2 t 3.33:.
5 9:...
.1i
1:7». .

t. .5
«1......
.

K‘. ‘0. .
a... .3. an
rt .... .2:

v....e..........u..‘u

4%,.

I":

.6...
.,

in?“

 

2.7.;

L.
.n.
.J.

 

 

[$28

 

-_—_.—-—n ‘u—v—I.‘ -—-

E SIS-'1. v a? 5" I. _-.‘-::. n

at? are-AF?!
;. 51:. . I . ‘ c _‘ in
53253! :“1 Sta 3.

U 8’} W33: raft}!

 

 

 

This is to certify that the
thesis entitled
MERCURY EMISSIONS FROM COAL—FIRED POWER PLANTS :

AN EVALUATION OF REDUCTION STRATEGIES
USING THE ANALYTIC HIERARCHY PROCESS

presented by

Julie C. Metty

has been accepted towards fulfillment
of the requirements for

M.S. degree in Resource Development

 

 

7 I V V
/ Major professor

Date November 17,. 2001

0-7639 MS U is an Affirmative Action/Equal Opportunity Institution

 

PIA

 

 

 

 

 

 

MERCURY EMISSIONS FROM COAL—FIRED POWER PLANTS:

AN EVALUATION OF REDUCTION STRATEGIES USING
THE ANALYTIC HIERARCHY PROCESS

By

Julie C. Metty

A THESIS
Submitted to
Michigan State University
In partial fulfillment of the requirements
for the degree of
MASTER OF SCIENCE

Department of Resource Development

2001

ABSTRACT
MERCURY EMISSIONS FROM COAL-FIRED POWER PLANTS:
AN EVALUATION OF REDUCTION STRATEGIES USING
THE ANALYTIC HIERARCHY PROCESS
By

Julie C. Metty

The US. Environmental Protection Agency (EPA) is currently developing mercury
emission regulations for the electric utility sector. AS is the case with most environmental
policy decisions, this is a complex undertaking. This research project evaluates a range of

mercury emission reduction strategies from a multi-objective perspective.

In-depth interviews and surveys were administered with representatives of the three key
stakeholder groups associated with this policy decision to determine their strategy
preferences and desired evaluation criteria. This provided the inputs to a multi-criten'a
decision analysis using the Analytic Hierarchy Process. The analysis revealed significant
differences among the stakeholder groups with respect to how they perceived the
alternative reduction strategies and the importance they placed on the various evaluation
criteria. The study revealed that certain reduction strategies could be eliminated from the
current strategy debate because they are not preferred by any of the three stakeholder
groups. In addition, a Strategy regulating multiple pollutant emissions at one time appears
to hold the greatest promise for achieving stakeholder consensus. It is also recommended
that the EPA employ a collaborative problem solving approach involving the key

stakeholders to further the policy debate and build consensus.

DEDICATION

This thesis is dedicated to Aaron, who deserves much more than being the subject of the
“dedication” section of my thesis for tolerating me through this ordeal called graduate
school. You thanklessly took care of me, believed in me, listened to my complaints,
hugged me, consoled me, and cheered for me every step of the way. Toward the end
when I was at my worst, you still loved me and, even more amazingly, proposed to me! I

will spend the rest of our lifetime together thanking you for your love and support.

iii

ACKNOWLEDGEIVIENT S

This thesis involved the collection of a considerable amount of data, which means that a
considerable amount of people voluntarily took the time to answer my questions and fill
out lengthy surveys. These individuals were not rewarded in anyway but with Simple

thanks, and I would like to thank them again for their considerable patients and time.

Additionally, I would like to thank my first and second major professors: Drs. Jeff
Riedinger and Cynthia Fn'dgen. Thank you both for your advice, patience, and guidance
during the confusion of my early years of graduate school. Dr. Riedinger also deserves
thanks for serving on my thesis committee, as does Dr. Emmett Braselton, who
introduced me to the complex world of toxicology. Thank you for your patience and time

in helping me understand the “science” behind the “policy.”

I went through three jobs, two moves, two major professors, and a great deal of
confusion, before I met Dr. Jo Ann Beckwith, who served as my major professor through
the last and toughest years of grad school. To her I owe the greatest thanks. Jo Ann was
strict enough to keep me on task, but kind enough to keep me from going crazy. In
academia, it is often hard to find a professor who still believes that their primary job
objective is teaching, but Jo Ann definitely prioritizes her Students and cares deeply about

their academic, professional, and personal success. I am lucky to have had her assistance.

Lastly, I want to thank my parents and friends, who are my true support system. Thank

you for always being there when l needed you and helping me get through this.

iv

TABLE OF CONTENTS

LIST OF TABLES ......................................................................... xiii
LIST OF FIGURES ............................................................................ ix
CHAPTER 1
PROBLEM ANALYSIS ........................................................................... 1
Problem Background ....................................................................... 1
Problem Statement ......................................................................... 2
Research Directions ........................................................................ 3
Outline of Thesis ............................................................................ 4
CHAPTER 2
PROBLEM FOCUSED LITERATURE REVIEW .............................................. 5
Environmental Decision Making ........................................................ 5
Multi-Criteria Analysis ......................................................... 9
The Analytic Hierarchy Process ...................................... 12
Toxicological Aspect of Mercury ....................................................... 15
Sources of Mercury in the Environment ....................................... 15
Mercury Fate and Transport ..................................................... 18
Mercury Exposure ............................................................... 19
Health Effects of Mercury Exposure .......................................... 20
Economic Impact of Mercury Pollution ....................................... 21
Mercury Reduction Policy ............................................................... 22
Regulatory Status of Coal-Fired Power Plants ............................... 22
Mercury Reduction Categories .‘ ................................................ 23
Existing Strategies Used to Reduce Mercury ................................ 25
Mercury Reduction Options for the Utility Sector .......................... 27
CHAPTER 3
RESEARCH DESIGN .............................................................................. 31
The Analytic Hierarchy Process ......................................................... 31
Phase One — Hierarchy Design ................................................. 32
Phase Two — Hierarch Evaluation ............................................... 39
Step One: Data Collection ............................................ 39
Data Collection Method ...................................... 41
Step Two: Relative Weight and Preference Calculation ........... 43
Step Three: Synthesis .................................................. 45
Step Four: Sensitivity Analysis ........................................ 46
Ethical Considerations .................................................................... 47
v

CHAPTER 4
RESEARCH FINDINGS AND ANALYSIS ................................................... 49
Hierarchical Design ....................................................................... 49
Utility industry responses ....................................................... 49
Environmental organization responses ........................................ 52
Government agency responses .................................................. 54
Hierarchy Structure design ..................................................... 55
Hierarchy Evaluation ...................................................................... 58
Survey response rate .............................................................. 59
Criteria weight and strategy preference results ................................ 59
Criteria importance weighting ......................................... 60
Utility industry results ......................................... 61
Environmental organization results ........................... 63
Government agency results ................................... 65
Paired comparisons of mercury Strategies ........................... 66
Utility industry results .......................................... 66
Environmental organization results .......................... 70
Government agency results .................................... 74
Priority synthesis results ................................................ 78
Utility industry results ........................................ 80
Environmental organization results ........................... 82
Government agency results ................................... 84
Strategy Preference Ranking ............................................................. 86
Utility industry strategy ranking ................................................. 87
Environmental organization strategy ranking ............................... 87
Government agency strategy ranking ........................................... 88
Sensitivity Analysis ..................................................................... 90
Utility industry sensitivity analysis ............................................ 96
Environmental organization Strategy ranking ................................. 97
Government agency strategy ranking ........................................ 100

CHAPTER 5
CONCLUSIONS AND RECOMMENDATIONS ............................................ 104
Selection of an Optimal Strategy ....................................................... 104
Optimization of the Multi-pollutant Strategy ........................................ 107
AI-IP and Group Decision Making ..................................................... 109
Suggestions for Further Study .......................................................... 110

APPENDICES

APPENDIX 1: TOXICOLOGICAL ASPECTS OF MERCURY ........................... 114
Environmental Chemistry of Mercury ................................................. 114
Mercury Fate and Transport ............................................................ 116
Sources of Mercury .................................................................. 121
Mercury Exposures and Threats to Human Health ................................... 126
Chronic Exposure Studies ............................................................... 137
Neurological studies ........................................................... 142

vi

Age at achievement of developmental milestones ......................... 142

Infant and preschool development ........................................... 144

Childhood development ........................................................ 145

Sensory, neurophysiological, and other en points in children ............. 147

Comparison of studies ......................................................... 148

Ecosystem and Wildlife Impacts ...................................................... 152
APPENDIX 11: PHASE I CONSENT FORM ................................................ 156
APPENDIX 1H: PHASE II CONSENT FORM ................................................ 158
APPENDIX IV: PHASE II SURVEY INSTRUMENT ...................................... 159
REFERENCES ..................................................................................... 173

vii

LIST OF TABLES

Table 1: Scale of Relative Importances/Preferences Used in this Study .................... 41
Table 2: Pairwise comparison matrix for level 2 ................................................ 44

Table 3: Pairwise comparison matrices for alternative priorities with respect to each

criterion ............................................................................................... 45
Table 4: Synthesized priorities ..................................................................... 46
Table 5: Survey response rates by Stakeholder group .......................................... 59
Table 6: Criteria weights for each stakeholder group .......................................... 61

Table 7: Utility industry strategy priorities with respect to evaluation criteria and final
preference weights. ................................................................................. 80

Table 8 : Environmental organization strategy priorities with respect to evaluation criteria
and final preference weights. ...................................................................... 82

Table 9: Government agency strategy priorities with respect to evaluation criteria and

final preference weights. ........................................................................... 84
Table 10: Comparison of strategy preferences generated by two approaches. ............. 86
Table 11: Government agency group Strategy preference ranking ......................... 89
Table 12: Major sources of human generated mercury releases in the US ................ 124
Table 13: Range of mean mercury concentrations in major fish species .................. 128

Table 14: “Safe” methlymercury concentrations in fish, based on EPA and ATSDR risk
approaches, and different consumption rates ............................................. 132

Table 15: Methlymercury concentrations in the top 10 types of fish consumed by the US
population .......................................................................................... 133

Table 16: Summary of epidemiological mercury exposure studies ........................ 138

viii

LIST OF FIGURES

Figure 1: Mercury contributions from anthropogenic sources in the US.

(EPA, 1997a) ......................................................................................... 17
Figure 2: Example of typical AHP hierarchy ................................................... 33
Figure 3: In-depth, semi-structured interview guide ....................................... 40

Figure 4: AHP decision hierarchy for identifying an optimal strategy to reduce mercury

emissions from coal-fired power plants .......................................................... 56
Figure 5: Comparison of evaluation criteria weights .......................................... 62
Figure 6: Utility industry group paired comparison results ................................... 67
Figure 7: Environmental organization group paired comparison results ................... 71
Figure 8: Government agency group paired comparison results ............................. 75
Figure 9: Comparison of overall strategy preferences ......................................... 79
Figure 10: Utility industry group overall strategy preferences ................................ 81
Figure 11: Environmental organization group overall strategy preferences ............... 83
Figure 12: Government agency group overall strategy preferences ......................... 85

Figure 13: Sensitivity of utility industry preferences to changes in compliance flexibility
criterion weight ..................................................................................... 91

Figure 14: Sensitivity of utility industry Strategy preferences to changes in planning
certainty criterion weight ......................................................................... 92

Figure 15: Sensitivity of utility industry strategy preferences to changes in political
feasibility criterion weight ....................................................................... 93

Figure 16: Sensitivity of utility industry Strategy preferences to changes in scientific
defensibility criterion weight ................................................................... 93

Figure 17: Sensitivity of utility industry strategy preferences to changes in legal
feasibility criterion weight ...................................................................... 94

Figure 18: Sensitivity of utility industry strategy preferences to changes in cost-benefit
criterion weight .................................................................................... 95

Figure 19: Sensitivity of environmental organization group strategy preferences to
changes in technological feasibility criterion weight ......................................... 97

Figure 20: Sensitivity of environmental organization group strategy preferences to
changes in legal feasibility criterion weight ................................................... 98

Figure 21: Sensitivity of environmental organization group Strategy preferences to
changes in political feasibility criterion weight .............................................. 99

Figure 22: Sensitivity of government agency group strategy preferences to changes in
technological feasibility criterion weight ........................................................ 100

Figure 23: Sensitivity of government agency group strategy preferences to changes in
legal feasibility criterion weight ........................................................ 101

Figure 24: Sensitivity of government agency group strategy preferences to changes in

political feasibility criterion weight ........................................................ 102

Figure 25: The mercury cycle ................................................................... 117

Figure 26: Mercury blood levels in the common loon ....................................... 152
x

CHAPTER 1

PROBLEM ANALYSIS

PROBLEM BACKGROUND

While legislative and policy decisions are often difficult to make and plagued by
complexity, environmental policy decisions have unique characteristics that pose even
greater challenges for decision-makers and affected parties. For example, decisions
regarding environmental policy usually involve uncertainty, require a great deal of
complex scientific input, create winners and losers with the distribution of costs and
benefits often unclear, and involve multiple actors who maintain diverse (and often
conflicting) interests, opinions, and values. One such pending environmental policy
decision follows the United States Environmental Protection Agency’s (EPA) December
15, 2000, decision to regulate mercury emissions from electric utility steam-generating
power plants. The EPA must choose a mercury control strategy for this sector and

finalize mercury emission regulations by December 15, 2004.

Mercury is a naturally occurring element that cycles in the environment as a result of
natural and anthropogenic activities. When mercury enters a water body, it may transform
to merthylmercury, which is a readily bioavailable form that efficiently biomagnifies in
the aquatic food chain. Methylmercury is highly toxic to humans and wildlife, who are

exposed primarily through consumption of contaminated fish (ATSDR 1999).

According to the EPA, electric utility steam generating units are the largest source of
anthropogenic mercury emissions in the United States, estimated to emit 43 tons of
mercury, or 1/3 of current US emissions (EPA 1999). During the last three decades
Significant controls have been placed upon the use and disposal of mercury from many
sources. However, the power plant sector lags far behind in terms of mercury reduction
efforts. Due to the adverse toxicological effects of mercury, and its persistence in the
environment, the EPA has determined that a policy solution that reduces the largest

anthropogenic source of mercury releases into the environment is needed.

PROBLEM STATEMENT

There are many possible mercury emission reduction frameworks that could reduce
and/or eliminate this source, including but not limited to fuel switching to cleaner burning
fuels or renewable resources, demand-side management, or installing pollution control
technology. Different reduction strategies have different implications in terms of
effectiveness, cost, feasibility, efficiency, cost distribution, and stakeholder acceptance.
Selecting one reduction strategy over another will involve trade-offs — trade-offs that
might be viewed as desirable by some stakeholders but be unacceptable to other
stakeholders. Therefore, a critical analysis of all possibilities is needed to determine
which strategy or combination of mechanisms is preferred overall or preferred from
specific stakeholder perspectives. The stakeholders in this case include well identified
interests including the electricity industry, government regulatory agencies such as the

EPA, and environmental groups engaged in this issue.

RESEARCH DIRECTIONS

The two main objectives of this research are:

1. To develop a multi-criteria decision framework for exploring and evaluating
alternative strategies for reducing coal-fired power plant mercury emissions; and
2. To recommend a preferred mercury reduction strategy for the coal-fired power

sector.

Questions to be addressed in the research include:

What mercury reduction strategies are preferred for the coal-fired power sector?
What are the major barriers to successfully implementing alternative mercury
reduction strategies?

What criteria should be used to evaluate different reduction strategies?

IS there common ground among the stakeholders in terms of their positions,
objectives and concerns regarding mercury reduction strategies for coal-fired power
plants?

What conflicting positions exist among the stakeholders and can any of them be
resolved?

What are the key trade—offs among the mercury reduction strategies and does any one
strategy or combination of Strategies have greater potential for Stakeholder acceptance
than the others?

What are the strengths and weaknesses of applying the Analytic Hierarchy Process in

this type of evaluation?

This analysis will provide guidance to the US. EPA regarding which mercury reduction

strategy they should apply now that a decision to regulate has been made.

OUTLINE OF THESIS

The broad scope of this chapter has been necessary to introduce properly the work
presented in this thesis, which is centered on the complex decision problem of how to
regulate mercury emissions from coal-fired power plants. In chapter 2, this background
information is expanded upon, including a detailed discussion regarding the factors that
contribute to the complexities and importance of this research problem. To accomplish
this, a three-section literature review is conducted to explore the different aspects of this
decision problem. The first section focuses on the characteristics of environmental
decision-making and the use of multi-criteria decision aids. The second section contains a
review of the literature on the toxicological aspects of mercury contamination that create
the urgency and need for issue resolution. The third section sets forth the options or

Strategies for mercury reduction identified in the literature.

Chapter 3 provides a detailed discussion of the research design used in this study, which
is modeled after the Analytic Hierarchy Process (AHP). This two-phased, multi-step
process is explained and examples are given to help the reader gain a full understanding
of the AHP and its role in multi-criteria decision making. In Chapter 4, the AHP model is
put into operation and results from the process are reported and analyzed. Chapter 5

contains a summary of the study and suggestions for future work.

CHAPTER 2
PROBLEM FOCUSED LITERATURE REVIEW

This literature review is broken into three sections. The first section focuses on the
characteristics of environmental decision—making and the use of multi-criteria decision
aids. The second section reviews the literature on the toxicological aspects of mercury
contamination that make it such an important issue to be resolved. The third section sets

forth the options or strategies for mercury reduction identified in the literature.

ENVIRONMENTAL DECISION-MAKING

An environmental decision is a decision concerning an issue or an action that could or
will have a foreseeable effect on the environment. Environmental decisions can vary in
many ways. They can occur at any administrative level (e.g., international, national,
state, city); be collective or personal in nature; be site-specific or program-related;
involve a positive or negative effect on the environment; and/or cause risk—benefit,

spatial, temporal or social dilemmas (NCEDR 1996).

While policy decisions in general are difficult to make, environmental policy decisions
have unique characteristics that make them even more difficult. According to the
National Center for Environmental Decision-Making Research (1996), aspects of

environmental decisions that make them more difficult include:

0 new Stakeholders are involved compared to traditional societal problems (especially
laypeople/affected people);

0 the problems often do not fit within administrative boundaries;

0 the distribution of costs and benefits is unclear;

0 the valuation of environmental assets (and hence options) is very difficult;

o more scientific input is necessary than for other sorts of problems;

0 the actions selected take a long time to realize;

0 they involve great uncertainty.

The mercury emissions issue possesses many of these characteristics. For example,
scientific uncertainty made the EPA’S decision regarding the regulation of mercury
emissions from the electric utility sector very complex. In 1990, Congress amended the
Clean Air Act and ordered the EPA to promulgate regulations establishing emission
standards for large sources of hazardous air pollutants, including mercury. Because of
the scientific uncertainty surrounding the level and health impact of hazardous air
pollutant emissions from the electric utility sector, Congress exempted this indristry from
regulation. Instead, Congress ordered EPA to study toxic hazardous air pollution from
power plants in order to determine if regulation was necessary in order to protect public
health. Several major studies (e.g. the EPA’S Mercury Study Report to Congress 1997,
the EPA’S 1998 Utility Air Toxics Study, the National Research Council 2000
Toxicological Effects of Methylmercury study) were published over the course of ten
years before a positive determination was made in December 2000, and the strategy EPA

will use to reduce mercury emissions will not be determined until 2004.

Mercury fate and transport tendencies also make it a difficult chemical to regulate due to
scientific uncertainty. In the atmosphere, most mercury is in elemental vapor form, which
can circulate for up to one year (EPA 1997a). This allows it to be transported long
distances from the original emission sources. Controlling the pathway of mercury is
difficult, because it cycles within the environment by moving between the air, water and
soil. Because there is no method to link deposition or ambient concentrations to exposure
concentrations for these pollutants, it is difficult to determine effective emission
reduction strategies. In addition, although the EPA has made estimations regarding
mercury emission amounts from different sources, these sources are quick to deny their
share of the mercury pollution problem because, they say, EPA’s estimates are flawed
and it is Still not scientifically clear exactly what their contribution is. Without this proof,

it is difficult to promulgate and enforce reduction strategies.

In addition to the decision-making obstacle scientific uncertainty presents, the global
circulation and unclear source contribution aspects of mercury emissions create
administrative decision-making difficulties. Mercury is a global problem, being emitted
by sources and deposited all over the world. Coordinating and reaching consensus on
environmental decisions involving different countries, cultures, econonries, and industries

is extremely difficult if not impossible.

Finally, uncertainty is a key obstacle in the decision to regulate mercury emissions.

There are many uncertainties involved in environmental regulation. Uncertainties that

exist in the mercury regulation issue include the effectiveness of different control
strategies, the appropriate target mercury reduction level to protect public health, what
the reduction strategies will cost, and whether the cost will be worth the benefit. For
example, requiring utilities to implement demand side management programs is
estimated to cost anywhere from $800,000 - $2.8 million per plant and has an unknown
reduction potential (EPA 2000a). All of these questions and uncertainties, particularly
regarding effectiveness and cost, complicate the mercury reduction decision-making

process.

The psychological aspects of decision-making, particularly with respect to the
environment, also contribute to the difficulty in designing and implementing policies with
broad public acceptance. Simply setting forth accurate factual information about an
environmental issue and its management options seldom meets with success in the public
arena because hey are viewed through a lens of beliefs, values and worldviews
(Bazerrnan et a]. 1997). Every individual has their own set of beliefs and values;
therefore, it is important to understand the psychology of individual and group action in
environmental domains in order to understand why environmental decision-making is so

complex.

The environment is a complex system of resource Stocks, providing a variety of valuable
service flows. Environmental resources, for the most part, are public goods, meaning
they are neither indivisible in consumption nor excludable in use (Perman et al 1996).

The implications of these two characteristics result in entitlement battles due to the

promotion of self-interest and exploitation of the resource. To compound these issues,
these valuable services to which everyone feels entitled are available in limited
quantities. Many environmental issues and conflicts revolve about the allocation of
resources (e.g. air, water, land) and deal with issues of both procedural and distributive
justice or notions of fairness (Knetsch 1997). They not only involve different interests
and feelings of entitlement, but different values as well. A person’s position on an
environmental issue is an expression of their fundamental values, beliefs, and ethics. It
touches on people’s core ideological beliefs (Thompson and Gonzalez 1997). The
environment is not just a conglomerate of resources to be allocated, but a symbol of
personal views and worldviews. These views can create major impediments to the

successful resolution of environmental disputes.

Matti-Criteria Analysis

Few decisions involve consideration of a single criterion. Even the most straightforward
question, such as which melon to purchase at the grocery store, involves multiple
objectives. The melon should be ripe, inexpensive, juicy, and large. Many times, these
objectives conflict, i.e. the ripest melon may be expensive, or the largest melon may be

less juicy, complicating the decision.

In many cases, a variety of conflicting factors and considerations must be weighed before
a feasible alternative is identified. The more multi-faceted a problem is and the more
conflicting the objectives are, the more difficult the decision—making process is and the

more necessary a decision aide becomes. When a decision-maker - whether they are a

grocery shopper, scientist, government official, or business leader - is faced with a choice
between alternatives, a mechanism for identifying the best solution is desirable. One

such mechanism is multi-criteria analysis (MCA).

MCA is a method employed by decision-makers to address a general class of problems
that involve multiple attributes, objectives, and goals (Zeleny 1982). An important
branch of applied mathematics and operational research, MCA is a decision making tool
that enables the rigorous selection of the most preferred alternative in a situation where
several criteria apply simultaneously (Mendoza and Prabhu 2000). There are many MCA
methodologies and approaches, such as the ranking method, rating method, and pairwise
comparison technique. Some more modern MCA tools incorporate these methodologies,
including data envelopment analysis, operational competitiveness rating analysis, and the

analytic hierarchy process (Parkan and Wu 2000).

MCA can aid in the decision-making process in a variety of ways (Beinat and Nijkamp

1998):

o MCA can be used to aid the identification of the most suitable solution from multiple
decision alternatives and environmental management options.

0 The effects of alternative decision options can be presented in a variety of forms, such
as monetary units, physical units, quantitative judgements, etc.

0 It brings out the positions, objectives and concerns of the decision actors, making it

possible to understand, justify, and negotiate the main issues involved in the decision.

This also enables the identification and resolution of potential conflicts at an early
stage of the decision process.

0 Trade-offs between different objectives and concerns are exposed, making it possible
to thoroughly analyze the pros and cons of different options.

0 It offers a framework for analyzing different choices against different future

scenarios.

The MCA concept received little attention until the late 1960’s. By 1970, MCA was the
fastest growing and most innovative of the operational research and management science
fields (Zeleny 1982). In the late 1970’s, a large variety of practical applications began to
appear, furthering its growth. More than 1,000 books and articles were written on MCA
and its applications during that decade, and the growth of its popularity continues. MCA
is not only established as one of the most dynamic and widely applied areas of
operational research and management science, it is now able to stand on its own and
bring its research results directly to practicing managers and decision makers. In fact,
most of the MCA activities take place outside and independently of the official
operational research and management science undertaking, including application in many
environmental management-related areas, including land use management, environmental

planning, waste management, and energy management (Zeleny 1982).

MCA is well suited to environmental management decision-making. Making
environmental management decisions involves interplay among a variety of human and

natural systems components. Often, due to differing interests and values, there is little

agreement among the various stakeholders as to what single factor or set of factors should
be used to or given more weight in evaluating and selecting among policy options. It is in
these types of multi-dimensional situations that multi-criteria analysis is valuable. For
instance in the land use arena, multi-criteria analysis is used to formulate indicators
encapsulating a wide diversity of attributes and environmental assets in a spatial setting
(Beinat and Nijkamp 1998). It facilitates multiple perspectives from multiple actors to be
addressed in planning decisions. MCA is helpful, in the presence of multiple concerns
and objectives, to analyze trade-offs between conflicting results, and search for

compronrise and acceptable environmental management solutions.

The Analytic Hierarchy Process

This study seeks to address a complex problem, which involves a multitude of possible
mercury reduction alternatives and evaluation criteria. Multi-criteria analysis can provide
a framework to tackle such a complex decision making environment. This method of
analysis provides a logical and systematic process for making better decisions in complex
decision situations with conflicting objectives, uncertainty, and different perspectives

(Leung et a1. 1998).

A recent addition to the multi-criteria analysis literature is the Analytic Hierarchy Process
(AHP), which provides a systematic and logical process for dealing with both
quantitative and qualitative data related to complex, multidimensional problems. It is
based on the principle that subjective judgments of the decision-maker are as important

as empirical data when making decisions. AHP is useful when neither logic nor intuition

12

alone is sufficient to determine which of several options are most desirable. As stated by
its founder, Thomas Saaty (1994, pg. 21), “AHP is about breaking a problem down and
then aggregating the solutions of all the sub-problems into a conclusion. It facilitates
decision making by organizing perception, feelings, judgements and memories into a
framework that exhibits the forces that influence a decision.” It is important to note that
AHP does not replace decision-making, but provides a conceptual framework for
systematic thinking about difficult problems along with a set of analytical tools to make

the decision-making process easier.

Less than three decades old, AHP has already created a voluminous body of literature in
many different fields as an innovative way to address multifaceted, complex problems.
The versatility of this approach has led to applications in many diverse areas. For
example Saaty (1990) provides a list of nearly 100 different applications up to 1990,
including energy resource allocation, policy/strategic planning, forestry management

decision-making, and environmental conflict resolution.

Decisions made using AHP occur in two phases: (1) hierarchic design and (2) evaluation
(Vargas 1989). Designing the hierarchy involves breaking the problem down into a
hierarchy of decision-making elements. The problem is modeled using a hierarchical
structure, as a tree containing the overall goal at the top, followed by a layer of subgoals
of the overall goal, then criteria and subcriteria that must be satisfied to fulfill the
subgoals of the overall goal. At the bottom of the tree is a set of policy alternatives.

Arranging the goals, criteria, and alternatives this way allows the decision maker(S) to see

the complex relationships inherent in the situation and assess the importance of each

issue at each level.

The literature cites the many benefits and disadvantages of AHP. Most users agree that
the major benefit of this method is its ability to facilitate complex decision-making by
organizing multiple perceptions, feelings, judgments, memories and data into manageable
decision-making elements (e.g. Vargas 1989, Hamalainen 1990, Saaty 1994). Some of
the most notable benefits found in the literature pertaining to AHP as a group decision-
support tool include:

1. AHP permits thorough modeling of the decision, inducing people to make
explicit their tacit knowledge; include judgements, intuition, emotion as well
as logic (Saaty 1994).

2. The use of pairwise comparisons forces AHP users to articulate the relative
importance of criteria and then to decide the relative contribution of the
alternative to the criteria (Carlsson and Walden 1995).

3. The sophistication and user-friendliness of Expert Choice software (Expert
Choice, Inc., 1996) allows AHP users to quickly build and solve a multiple
criteria decision problem (Carlsson and Walden 1995).

4. The hierarchical feature of AHP allows easy and natural structuring of the
problem so that the user can clarify and consider all the relative, diverse

problem aspects (Carlsson and Walden 1995, Hamalainen 1990).

5. AHP is practical in that the decision-maker is free to remain inconsistent, but
receives feedback on the frequency and level of inconsistent judgements

(Hamalainen 1990).

Carlson and Walden (1995) pointed out four weaknesses of the AHP as a decision-
support system pertaining to group decision making:

1. AHP users almost never use the seven (very strong importance) and the nine
(extreme importance) scale because they do not perceive them to be much
different from five (essential or strong importance).

2. AHP users must rely too heavily on their experience and intuitive judgement.

3. An arbitrary starting reference point is needed in pairwise comparison that may
change perceptions of a multiple criteria problems.

4. Pairwise comparisons eliminate the longer chains of interdependence, which

the users perceive during an AHP evaluation.

TOXICOLOGICAL ASPECT OF MERCURY

Sources of Mercury in the Environment

Mercury is a naturally occurring element that, like all elements, exists in the same
quantities now as when the Earth was first formed. Geologically bound mercury can be
mobilized or released to the environment by natural processes or human activities, and
can also be re-emitted. Natural mechanisms for mercury emission to the environment
include volatilization from soils, aquatic environments, and vegetation, as well as

volcanic and other geothermal activities (Nriagu 1979). Anthropogenic sources of

mercury include metal production, chlor—alkali and pulp industries, waste handling and
treatment, and coal, peat, and wood burning (EPA 1997a). Re-emitted mercury includes
transfer of previously deposited mercury (released naturally or anthropogenically) to the

atmosphere via biological and geological processes'.

Although a great deal of uncertainty remains, it has become increasingly evident that
anthropogenic emissions of mercury rival or exceed natural inputs. According to EPA’s
Mercury Report to Congress (1997b), the amount of mercury mobilized and released into
the environment has increased by a factor of between two and five since the beginning of
the industrial age. Current estimates suggest that 50-75 percent of the total yearly input of
mercury into the atmosphere from all sources is the result of anthropogenic releases. A
recent paper reported estimates of global anthropogenic mercury emissions reaching as
high as 71 percent of total mercury emissions if re-emitted anthropogenic mercury is

considered in the estimates (Jackson 1997).

The most recent total annual estimate for all anthropogenic mercury emissions to the air
in the US. was 158 tons (316,000 pounds) (EPA 1997a). While this estimate has a
number of uncertainties, it is likely low, due to lack of full accounting for mercury use at
chlor-alkali plants, underestimation of previously emitted mercury that is deposited and
re-mitted from soils, water, or plants, and possibly other poorly-characterized sources

(i.e. mobile source emissions).

 

' The fluxes of re-emitted mercury to the atmosphere are not clearly established: more study in this area will be required to document
and assess this potential secondary source. which can contribute to long-term cycling of mercury in the environment.

16

In its mercury report to Congress, the EPA characterized the percentage contribution of
mercury emissions from US. anthropogenic sources (see Figure l). The EPA believes
that 86 percent of these emissions comes from processes that result in the combustion of
mercury-containing material, including municipal waste combustion (19 percent); coal
and oil-fired commercial/industrial boilers (18 percent); medical waste incinerators (10
percent), hazardous waste combustion (4 percent); and residential boilers (2 percent).
Coal—fired electric utilities are the single largest source of mercury pollution in the US,
responsible for 33 percent of the total mercury emissions from all sources. These plants
release mercury when burning coal for fuel, which contains trace amounts of mercury.
The EPA estimates that the industry emitted 43 tons of mercury in 1999 from 1,149 units

at 464 coal-fired plants (EPA 1999b).

Figure 1: Mercury Contributions from United States Anthropogenic
Sources (EPA, 1997!!)

 

   

Oommrc iall
hdustrial Boilers ' Mrnicipal Wast hc'neration
18% 19%

 

 

 

Mercury Fate and Transport

Mercury can be discharged directly to land and water through industrial wastewater
releases or the disposal of waste-containing batteries and other sources of mercury.
However, because of the relatively volatile nature of mercury and the way in which it is
released, a much larger fraction of total releases to the environment consist of releases to
air. Air emissions are transported through the atmosphere and eventually deposit onto
land or water bodies. Scientists now believe that atmospheric deposition is responsible

for the bulk of mercury loading to terrestrial and aquatic ecosystems.

Mercury deposition can occur very close to the source or, depending on the chemical
form in which it is emitted, it can be transported great distances - even crossing
international borders. The highest deposition rates in the US. occur in the southern Great
Lakes, the Ohio Valley, the Northeast and scattered areas in the Southeast.
Approximately 60 percent of the mercury deposition that occurs in the US comes from
domestic human-made sources of pollution. The remaining 40 percent comes from
human-made sources located outside of the US, re—emitted mercury from historic U.S.
sources, and natural sources. Based on estimates of the total annual input of mercury to
the atmosphere from all sources (i.e., 5000 Mg from anthropogenic, natural, and oceanic
emissions), U.S. sources are estimated to contribute 52 tons (EPA 1997b). While this is
only about 3 percent of the global atmospheric pool of mercury, the US. still contributes
more than it receives. Approximately two-thirds of US. emissions are transported outside

our borders (EPA 1997b).

18

Once mercury enters waters, either directly or through air deposition, it can
bioaccumulate in fish and animal tissue in its most toxic form, methylmercury. Mercury
is so efficiently bioaccumulated in the aquatic food web that the concentration of mercury
found in predators at the top of the food web (for example, predatory fish and fish-eating
birds and mammals) can be thousands or even millions of times greater than the

concentrations of mercury found in the water.

Mercury Exposure

For the general US. population, the dominant pathway for human and wildlife exposure
to mercury is the consumption of fish, marine mammals, and crustaceans (NRC 2000).
Women of childbearing age, and people who regularly and frequently eat highly
contaminated fish (or large amounts of moderately contaminated fish), are the most likely
to be at risk from mercury exposure. Those groups include subsistence fishermen (people

who fish for their food) and some Native American populations.

Freshwater fish (caught by recreational or subsistence fishermen) from contaminated
waters have been shown to have particularly high levels of methylmercury. Mercury
contamination is the most frequent basis for fish advisories. Because of the health hazards
associated with mercury and the levels of mercury detected in fresh water fish, health
officials have issued fish consumption advisories in thousands of water bodies
nationwide, including all of the Great Lakes and their connecting waters — more than
52,000 lakes and more than 238,000 miles of rivers. As of July 2000, 40 states and one

territory (American Samoa) had issued fish consumption advisories for mercury. Of those

states, 13 have issued state-wide advisories, covering every inland lake and Stream; the
remaining 27 states issued advisories for more than 1,900 Specific water bodies (EPA

2000).

High mercury levels also have been found in certain saltwater fish. In March 2000, for
example, Florida, Georgia, North Carolina and South Carolina issued a joint fish

consumption advisory because of high mercury levels in large king mackerel.

Certain species of commercially available saltwater fish, such as shark and swordfish,
also have high levels of mercury. The US. Food and Drug Administration (FDA) issues
consumption advice for commercial marine fish. The FDA plans to re-evaluate its current
advice in light of a July 2000 report by the National Research Council that confirmed
EPA's mercury reference dose, i.e., the level at which people could be exposed to

mercury without the risk of health problems.

Health Efl'ects of Mercury Exposure

The National Research Council July 2000 report completed a review of the latest
scientific evidence regarding the health effects of methylmercury. Methylmercury causes
a wide range of adverse effects in multiple organ systems throughout the life span of
exposed humans and wildlife. In humans, epidemics of mercury poisonings following
high-dose exposures in Japan and Iraq demonstrated that the fetal central nervous system

is the organ widely viewed as the most sensitive to mercury exposure.

20

The database on neurodevelopmental effects is extensive and includes studies
documenting neurological dysfunction and developmental abnormalities that occur
following both acute and chronic mercury exposure. Ingested methylmercury is almost
completely absorbed into the blood and distributed to all tissues (including the brain); it
also readily passes through the placenta to the fetus and fetal brain. Children born of
women exposed to relatively high levels of methylmercury during pregnancy are at
special risk of neurological problems and have exhibited a variety of developmental
neurological abnormalities, including delayed onset of walking and talking, cerebral
palsy, and reduced neurological test scores. Far lower exposures during pregnancy have
resulted in delays and deficits in learning abilities in the children (NRC 2000). This data

confirmed EPA’s assessment of the health risks related to mercury exposure.

Mercury also poses risks to fish-eating wildlife, including some birds and mammals, such
as the loon, mink, and otter. Adverse effects include death, reduced reproductive success,

impaired growth and development, and behavioral abnormalities (EPA 1997c).

Economic Impact of Mercury Pollution

The contamination of our waterways and fish, and the health risk it imposes on people
and wildlife, are not the only threats mercury poses. Mercury contamination also
threatens the health of our economy. Sport fishing plays a significant role in the lives of
over 35,245,000 American adults. A substantial industry has evolved to provide goods
and services to meet the diverse needs of the nation’s anglers. U.S. anglers who went

fishing during 1996 spent nearly $37.8 billion for goods and services in many businesses

21

throughout the country. The economic impact of these expenditures totaled nearly $108.4
billion and rippled throughout the economy with effects felt at the local, regional and

national levels (American Sportfishing Association 1998).

MERCURY REDUCTION POLICY

Regulatory Status of Coal Fired Utilities

When Congress amended the Clean Air Act in 1990, they ordered the EPA to promulgate
regulations establishing emission standards for each category or subcategory of major
sources and area sources of hazardous air pollutants, including mercury. Although
electric utilities met the definition of a major source, they were expressly exempt from
regulation. Instead, Congress ordered EPA to study toxic hazardous air pollution from
power plants in order to determine if regulation was necessary in order to protect public

health (CAA Section 112(n)(l)(A) 1990).

As part of the regulatory finding process, the EPA published two reports to Congress in
1997. The first was the Utility Air Toxics study, which identified mercury emissions
generated by coal-fired utility boilers as the hazardous air pollutant of greatest concern to
human health of all emissions from this source. The Mercury Report to Congress was the
second report, and it identified coal-fired power plants as the largest source of
anthropogenic mercury emissions in the US, accounting for one-third of all emissions in

the country.

22

To further inform the mercury regulatory decision, using the authority of section 114 of
the Clean Air Act, the EPA requested information from all coal-buming power plants
regarding the mercury content of the coal they burn. Certain plants were also required to
test the amount of coal being emitted from their plant. The data gathering, officially
called an Information Collection Request (ICR), occurred throughout 1999. The purpose
of the ICR was to collect enough information to improve estimates of the amount of
mercury being emitted by coal-fired power plants. The analysis of the data collected
concluded that coal-fired power plants are a major source of mercury emissions,

responsible for 43 tons of the mercury emitted in 1999 from 1,149 units at 464 plants.

Additionally, at the direction of Congress, the EPA funded the National Academy of
Sciences to perform an independent evaluation of the available data related to the health
impacts of methylmercury. This study confirmed the EPA’s assessment of the health and
environmental hazards caused by mercury. On December 14‘“, 2000, EPA announced that
it had decided that mercury air emissions from power plants Should be regulated because
they are the largest source of anthropogenic mercury emissions in the country and, of all
the hazardous air pollutants emitted from this source, mercury poses the greatest health
risk. EPA plans to propose a regulation to control air toxics emissions, including
mercury, from coal- and oil-fired power plants by the end of 2003 and will issue final

regulations by December 2004.

Mercury Reduction Categories
Options for mercury reductions fall into several categories, ranging from alternatives that

completely eliminate the possibility of mercury contamination, to those that reduce

23

contamination and/or the likelihood of contamination (EPA 2000a). These categories

include:

o Substitution: Using alternative products or process inputs that are mercury free and
either less toxic than mercury or non-toxic. For example, using renewable resources
to generate electricity rather than coal would completely eliminate mercury emissions
associated with electricity production.

0 Recycle/Safe Disposal: Ensuring proper handling of products containing mercury
when end of useful life is reached to guarantee minimal or no air or water
contamination.

0 Energy Efficiency/Conservation: Reducing or eliminating the demand for mercury
products or process inputs. For example, increasing energy efficiency in appliances
and windows reduces energy consumption and, therefore, reduces energy production
by—products (i.e., mercury emissions).

0 Mercury Reduction Technology: Where mercury is a pollution by-product of
manufacturing, energy generation, or waste disposal, in-process or end-of-pipe
control technologies can be effective in reducing emissions of mercury and other
hazardous substances. The US. Department of Energy is currently funding five
projects that explore different control technology approaches to reducing mercury and
fine particulates from coal-fired utility boilers, including dry carbon-based sorbent
injection and high efficiency electrostatic precipitators (DOE 2000).

O Remediation: When mercury spills occur (in a classroom science lab, for example),
proper spill response planning and clean-up (followed by proper disposal) can help

reduce the severity of the contamination.

24

0 Education: Informing the general public about the hazards of mercury reduces the risk
of mercury exposure to people and the environment. Education can also lead to a

greater willingness to engage in demand side management activities.

Existing Strategies Used to Reduce Mercury

The leading sources of mercury are well defined and, during the last three decades,
voluntary efforts have been made to reduce mercury releases and significant controls
have been placed upon the use and disposal of mercury from many sources. For example,
there have been many regulations created by the EPA to address mercury and its release
into the environment. Mercury releases to the air are governed in the United States by the
Clean Air Act, under which mercury and mercury compounds are considered Hazardous
Air Pollutants (HAPS). Recently, the EPA established National Emission Standards for
Hazardous Air Pollutants (NESHAPS) for mercury emissions, which cover three specific
source categories: ore processing facilities, mercury cell chlor-alkali plants, and sewage

sludge dryers.

Under the Clean Air Act Amendments of 1990, the EPA regulates HAPS emissions by
source category. The Act requires EPA to regulate all categories of “major sources,”
which it defines as any source that releases ten tons per year of any one HAP, or 25 tons
per year in total HAP emissions. Sources regulated under the Act’s “major source”
provision include chemical manufacturers, ore processing facilities, and pulp and paper
mills. These and other major sources are subject to Maximum Achievable Control

Technology (MACT) standards. The EPA has developed MACI‘ standards for many

25

sources including hazardous waste incinerators and medical waste incinerators, which

call for a 50 percent reduction of mercury emissions over the next five years.

In addition to federal regulations, many states and cities have enacted laws to reduce
mercury contamination. For example, Minnesota has banned the disposal of fluorescent
lamps, requiring all businesses and household to recycle these mercury-containing
products. New Hampshire passed a law in June 2000 prohibiting the sale of certain
mercury-added products, establishing notification and disclosure requirements for
permissible mercury-containing products and establishing limitations on the use of
elemental mercury. Within the last year, San Francisco, California; Duluth, Minnesota;
and Ann Arbor, Michigan; DeForest, Stoughton and Dane County, Wisconsin; and
Boston, Massachusetts passed ordinances banning the retail sale of mercury

thermometers.

Regulation is not the only mechanism means by which mercury reductions have been
made. Many businesses and organizations have established voluntary programs to help
curb the amount of mercury releases. Health Care Without Harm is a non—profit
collaborative organization that encourages environmentally responsible health care
practices. Their “Mercury Free Medicine” campaign awards hospitals that pledge to
phase out the use of mercury-containing products. So far, 584 medical facilities have
pledged to go mercury-free (NWF 2000). In December 1997, the Thermostat Recycling
Corporation (TRC) launched a program to recycle mercury-switch thermostats in nine

states. The TRC is a private corporation established by thermostat manufacturers

26

Honeywell, General Electric, and White-Rodgers. Since the program's inception, TRC
has recycled 274 pounds of mercury from thermostats. TRC collected and processed

more than 110 pounds of mercury in the first six months of 1999 (EPA 2000b).

Mercury Reduction Options for the Utility Sector
Pollution control strategies for coal-fired utilities fall into three categories: pre-

combustion, post-combustion, and energy efficiency/conservation (EPA 2000a).

Pre-combustion techniques for reducing mercury emission are utilized in the process

before fuel is burned to produce energy. These methods employ chemical, biological, or

other alternative techniques to remove, or reduce the possibility of, high percentages of
ash. There are four techniques that fall under this category.

0 Coal Cleaning: Mechanical devices using pulsating water or air currents are used to
physically stratify and remove the ash components that are imbedded in the coal,
which contain trace minerals including mercury. This is done before the coal is
crushed and introduced into the boiler (EPA 1997d). This technique also reduces acid
rain-related emissions of sulfur dioxide and other hazardous air pollutants.

0 Coal Switching: Switching from coal that is high in mercury per Btu to one that is
low in mercury per Btu can reduce mercury emissions (CCAP 1998). Switching from
one source of coal to another can also reduce emissions due to changes in coal
characteristics that improve the mercury collection efficiency of existing control

equipment (MPCA 2000).

27

 

Fuel Switching: This option involves switching to a less polluting fuel source to
achieve desired mercury reductions. Not only would switching to cleaner fuels,
including natural gas and renewable resources, eliminate emissions of mercury, but it
would also largely eliminate particulates, other heavy metals, sulfur dioxide, and also
reduce nitrogen oxides and carbon dioxide (EPA 2000a).

Co—Firing: A percentage of coal burned at existing power plants is replaced with

cleaner fuel sources, such as natural gas and wind power.

Post-Combustion technologies clean flue gases that are emitted from coal burning. They

are generally located in the ductwork leading to the smokestack. Examples include:

Wet Scrubbing: Scrubbers are currently used to remove sulfur dioxide on about 25
percent of the coal-fired utility generating capacity in the US (Center for Clean Air
Policy 1998). This technique also has been Shown to remove mercury from the flu
gas.

Electrostatic Precipitators: These are the most frequently used particulate matter
control device on utility boilers. They remove particulate-bound mercury.

Carbon Injection: This technique involves the direct injection of activated carbon into
the flue gas Stream of a utility boiler. The activated carbon is porous and, therefore,
has a high surface area, allowing it to absorb a broad range of mercury and other trace
contaminants (EPA, volume VIII 1997). The used carbon and attached mercury are
then captured by existing particulate matter controls, such as an electrostatic

precipitator, and disposed of in ash ponds or landfills.

28

0 Carbon Filter Beds: Rather than injecting carbon into the flue gas, the flue gas is

evenly distributed throughout a bed of carbon.

Energy efficiency involves the implementation of strategies that increase the efficiency of
energy production and/or decrease the demand for energy use. Energy efficiency and
conservation practices offer many benefits for energy producers, consumers, and the
environment. These practices lower energy production—related emissions; provide energy
cost savings to consumers and businesses; preserve fuel supplies; and enhance utility
profits by increasing productivity and reducing energy and material use, disposal costs,
and environmental compliance costs. In its State Scorecard on Utility Energy Efficiency
Programs, the American Council for an Energy-Efficient Economy concluded that
electric utilities could save up to 100,000 megawatts of electrical demand by tuning up
residential air condition systems and installing more efficient air conditioning systems
and lighting in the commercial sector. This could be enough savings to stall the need to

build new power plants to meet increased electricity demand throughout the next decade.

Opportunities for energy efficiency and conservation include:

0 Demand-Side Management: Demand-side management (DSM) programs consist of
the planning, implementing, and monitoring activities of electric utilities which are
designed to encourage consumers to modify their level and pattern of electricity usage
(DOE 1997). They can entail energy efficiency measures that enable consumers to
perform the same function with less energy, such as the installation of energy saving

appliances and lighting, or load-management programs that reduce demand during

29

peak loads, such as entering into contractual arrangements with customers who can
self-generate power.

Co—Generation: Producing heat and electric power simultaneously improves the
efficiency of electric production and overall energy use by recapturing waste heat that
would otherwise be exhausted. Co—generation extracts much more usable energy
from the same amount of fuel. This can be done in a number of ways, but most
commonly involves using waste heat from the steam or a hot water line to generate
electricity (M2P2 1996).

Alternative Policy Approaches: Alternatives to traditional command-and-control
regulation can provide environmental benefits and cost savings by achieving the
largest pollution reduction at the lowest cost. Such alternatives may be divided into
three categories: (1) performance Standards such as Emissions Cap Programs where a
ceiling of allowable emissions is set and there is flexibility regarding how the limits
are met; (2) information strategies such as a “Right-to-Know” program where
mercury emission levels are made available to the public creating an incentive for the
polluting industry to be a “good neighbor" and reduce; and (3) market incentive
approaches such as a mercury emissions trading program. A prominent example of
market-based incentives to achieve environmental protection in use today is the sulfur
dioxide emission-trading program where sulfur dioxide emission allowances are
traded between industries to reduce acid rain. See http://www.epa.gov/airmarkets for
more information regarding EPA’S Acid Rain Program and other market—based EPA

regulatory programs.

30

CHAPTER 3

RESEARCH DESIGN

This chapter presents the research design, subjects, evaluation procedures, and ethical
considerations used to assess which strategy stakeholders prefer to reduce mercury

emissions from coal-fired power plants.

THE ANALYTIC HIERARCHY PROCESS

This research study uses a multi-criteria analysis method known as the Analytic
Hierarchy Process (AHP), as originally formulated by Thomas Saaty (Saaty 1980), to
evaluate mercury reduction strategy preferences among a diverse set of stakeholders.
Although there are many different multiple criteria decision aids that could be applied to
this study, AHP was chosen because it provides an appropriate decision-making
framework for the problem at hand. The benefit of using this method is improved
efficiency and results for group decision-making. As an approach, it encourages
compromise and consensus building among diverse interest groups. This is achieved by
AHP’S unique ability to allow criteria to be considered individually and aggregated into
overall preferences. AHP is simple in construct, yet extremely powerful. It is also
practical, as it does not require inordinate specialization to master and communicate and

utilizes readily available and user-friendly decision support software.

31

AHP implementation has two sequential phases. Phase one is the process of designing the
decision hierarchy, which involves decomposing the decision problem into a hierarchy of
interrelated decision elements (goal, evaluation criteria, and solution alternatives). The
second phase is the evaluation of the hierarchy, which is a four-step process:
1) Collecting input data (judgments) by pairwise comparisons of the decision
elements,
2) Calculating relative weights of the decision elements to determine local
priorities,
3) Synthesizing the relative weights and priorities to deterrrrine the best
alternative,

4) Analyze sensitivity to changes in judgment.

Phase One: Hierarchy Design

The first step in applying AHP to a decision problem is to break the problem down into a
hierarchy of interrelated decision elements (Saaty 1980). An overall goal or objective is
placed at the top of the hierarchy, which is followed by lower levels of evaluation criteria
that contribute to the quality of the decision. The lower the hierarchy level, the more
detailed the criteria. The number of hierarchy layers depends on the complexity of the
problem and the degree of detail the researcher requires to solve the problems. For the
purposes of this study, a three layer hierarchy will be used. The last level of the hierarchy
contains the alternatives or solution choices. Arranging the goals, criteria, and

alternatives this way allows the decision maker(s) to see the complex relationships

32

inherent in the Situation and assess the importance of each issue at each level. The

standard design of an AHP decision hierarchy is depicted in Figure 2.

Figure 2: A general presentation of a decision hierarchy for AHP

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Most General Goal of
_ Decision Problem
“E2 '5
3 8
2 Decision Decision Decision
4; Criterion 1 Criterion 2 Criterion 3
.3 Cd
':
33
'I:
m U More Detailed More Detailed More Detailed
1;; Decision Decision Decision
3 Attribute l Attribute 2 Attribute 3
g »6""/\
% ~ / v, V .
E E Alternative 1 Alternative 2 Alternative 3 Alternative 4
2‘

 

 

To begin structuring the hierarchy for this study, the researcher first identified the overall
goal: to reduce mercury emissions from coal-fired power plants to a target level. This was
determined by exploring the overall question behind the thesis research topic selected.
The remaining hierarchy decision elements were determined using a two-step process.
First, a literature review was conducted to aid in the decomposition of the decision

problem by exploring different existing mercury reduction strategies. As stated in the

33

literature review above, the literature revealed three basic mercury reduction categories
(EPA September 2000):
O pre-combustion techniques, which are utilized in the process before fuel is burned
to produce energy;
0 post-combustion technologies, which clean flue gases that are emitted from coal
burning; and
0 energy efficiency, which involves the implementation of strategies that increase

the efficiency of energy production and/or decrease the demand for energy use.

The second step in determining the decision elements of the hierarchy involved
conducting interviews with experts in the issue area. This second step was implemented
to strengthen the overall design of the hierarchy, but is not required by the AHP. In fact,
many different examples of hierarchy construction techniques can be found in the
literature. For example, the researcher can construct the hierarchy alone, selecting the
goal, criteria, and policy alternatives based on independent knowledge or a review of the
literature. Another technique involves a group approach, where stakeholders brainstorm
together to design the hierarchy. This group approach was applied successfully by Leung

et al (1998) to address a complicated fishery management policy decision in Hawaii.

In this research study, it was believed that using only one expert to design the mercury
reduction strategy hierarchy would have implanted a weakness in the design because of
the inherent risk of subjectivity, e.g. two different experts could Structure the same

problem differently, yielding two different choices of action. To ensure the integration of

34

appropriate decision elements, decrease the level subjectivity, and provide credibility to
the overall research design, a series of in-depth interviews were conducted with a range

of key, expert stakeholders.

The in-depth, semi-structured interview is a qualitative interviewing technique that
involves asking informants open-ended questions, and probing wherever necessary to
obtain data deemed useful by the researcher. Unlike quantitative interviewing, which
typically involves the use of a structured survey instrument that asks all respondents the
same questions about their attitudes and behaviors, the in-depth, semi-structured
interview has Specific objectives to cover within the course of the interview and the

researcher is permitted some freedom in meeting them (Berry 1999).

This interview style was chosen for this study because of its ability to elicit information
that results in a holistic understanding of the interviewee’s point of view. Also, it allows
the respondent to freely speak more in his or her own words with regard to the topic of
interest, allowing the interviewer to adapt the interview to capitalize on the Special
knowledge, experience or insights of respondents. These benefits result in more complete

information and a more thorough investigation.

Although there are many benefits to the in-depth, semi-structured interview technique
that have made it the obvious choice for this research endeavor, there are disadvantages
to this technique as well. Because the researcher is gaining information from the

informant, as opposed to direct observation, the researcher’s findings are open to the

35

vagaries of the informant’s interpretation and perception of reality (Minichiello et al
1995). Whereas participant observation enables the researcher to directly observe the
informant in his or her everyday life, resulting in a richer understanding of the
informant’s perspective, researchers using the in-depth interview technique are limited to
the informant’s situational perspective, thus deprived of the ethnographic context.
Although this may seem like a substantial method weakness, it can be overcome by
adopting intrusive yet ethically sound methods. A high level of interaction with the
informant during the interview process will increase the validity of the data gathered.
Some researchers dismiss this weakness altogether, stating that during the interview the
informant is operating within an ethnographic context, and it is from this context that the

informant makes decisions about what to say (Minichiello et a] 1995).

In this study, the purpose of the interviews was to:
(a) identify any additional mercury reduction strategies to add to the preliminary list
identified in the literature review;
(b) identify evaluation criteria to be applied in the multi-criteria analysis; and
(c) gain insight to the values and beliefs systems that underpin the stakeholder's

position on the issue of mercury reduction strategies.

The individuals selected to identify the policy alternatives and evaluation criteria

elements for the hierarchy can be divided into three different interest groups, all who hold

a key position in the mercury emissions debate. These groups are environmental

36

organizations (four interviews conducted), governmental agencies (five), and the electric

utility industry and associated research organizations (four).

The individuals selected to represent the environmental organization stakeholder group
have had a long history of working specifically on reducing the environmental damage
caused by power production, particularly with regard to mercury emissions. Each
interviewee were selected on the basis of their policy expertise and pre-existing
knowledge of the mercury emissions issue. Their involvement in the issue spans from
grass roots organizing to decision-maker education to policy analysis to assisting in
regulation oversight and creation. These individuals have either advanced legal or

scientific backgrounds.

Government agency representation can be divided into two areas: regulatory policy
creation and pollution technology research and development. The five government
agency employees were selected because of their past and present involvement in either
the mercury regulatory determination itself, or research and development of mercury
control technologies for the utility sector. All government agency interviewees have a

long history of working for their respective organizations and on this issue in particular.

The individuals representing the utility sector interests are either employed by a specific
utility company or a nonprofit electric power research organization. These individuals
have been selected because of their scientific, technical, and/or legal background working

with the issue of mercury emissions from coal-fired power plants. Those employees

37

interviewed from the utility companies are environmental scientists that investigate
mercury emissions and controls on behalf of their employer. Individuals representing
electric power research organizations research science, emission control technology, and

policy options for the energy service industry.

One additional interview was held with a representative from a Washington D.C.-based
non-partisan research organization to gain an additional informed expert opinion. This
person has an extensive background in the research area and was used as because of their
research and experience in identifying cost-effective approaches to reducing mercury
emissions associated with electric power generation. This individual represents a
nonprofit organization, which investigates solutions to environmental problems with a

goal of reaching common ground between diverse and conflicting interests.

The interviewee recruitment process began with electronic mail message sent to
perspective respondents informing them that a letter would be coming via US. mail
requesting their participation in a university research effort. The letter contained
information regarding the research purpose and procedure. The letter also informed the
interviewee that their participation was voluntary, and that their identity and responses
would be kept confidential. The interviewees were asked to Sign and return the letter,
indicating their consent to participate, in a postage-paid return envelope (provided). Once
the letter was received, a telephone call was placed to deterrrrine an interview time that
was convenient for the interviewee. Phone calls were placed at the agreed upon time and

respondents were asked if their interviews could be audiotape recorded.

38

The qualitative interviews were conducted during March 2001 and were generally one
hour in length. Following the in-depth semi-structured interview paradigm, an interview
guide was used to ensure the above issues have been addressed and consistency in topic
coverage across the interviews. However, because of the nature of the semi-structured,
in-depth interview technique, the subject’s responses often lead to further probing
questions in addition to those listed in Figure 3. An attempt was made to encourage
interviewees to freely volunteer information as opposed to asking for responses to close-
ended questions. At the end of the interview, respondents were thanked for their
participation and were instructed how to contact the researchers if they had questions or

comments.

Phase Two: Hierarchy Evaluation
The next phase of AHP implementation is the evaluation of the hierarchy that, as stated

above, is a four-step process.

Step One: Data Collection

Step one involves eliciting judgments that reflect the opinion of the stakeholders involved
in the decision problem. A judgment is the numerical representation of a relationship
between pairs of decision elements in the decision hierarchy. These pairwise comparisons
are made by asking the question: “Which of the two elements is more important with

respect to the next higher level element, and how strongly?” Paired comparisons allow

39

the relative weights of decision elements to be obtained by having decision makers focus

on a pair of two decision elements at a time (Ra 1999).

Figure 3: In-Depth, Semi-Structured Interview Guide

 

 

STAKEHOLDERS’ MERCURY REDUCTION STRATEGIES
AND EVALUATION CRITERIA

INTERVIEW GUIDE
1. In your opinion, what strategy do you favor for reducing the amount of mercury that
is emitted from coal-fired power plants?

2. If you had to list a number of alternative approaches to reducing mercury emissions
from coal-fired power plants, what would be on that list?

3. If you worked for the US. Environmental Protection Agency, for example, and had to
develop a reduction strategy for mercury emissions from coal-fired power plants,
what strategy would you choose? Why?

4. On what basis should decisions regarding mercury reduction strategies be made?

5. What aspects of the mercury reduction strategies you put forward do you like the
best? What aspects do you like least?

6. What reduction strategy for mercury emissions from coal-fired power plants are you
aware of, but disagree with? Why do you not favor these strategies?

7. Who else would you recommend interviewing?

Note: This is a list of general topics that, at a minimum, will be covered consistently
with all subjects across all interviews. Because of the nature of the semi-structured, in—
depth interview technique, the subject’s responses may lead to further probing questions
in addition to those listed above.

 

40

 

Each paired comparison is represented in a square matrix in which the decision elements
are compared with respect to the level avove it in the hierarchy. The intensity of relative
importance/preference levels are measured using a fundamental scale of the number set:

{9, 8, 7, 6, 5, 4, 3, 2, 1, 1/2, l/3, 1/4, 115, 1/6, 1/7, 1/8, 1/9,} (see also table 1).

Table 1: Scale of Relative Importances/Preferences Used in this Study2

Intensity of

 

 

 

 

 

 

 

 

 

lnr[romance/Preference Definition
1 Equal importance/preference
3 Moderate importance/geference
5 Strong importance/preference
7 Very strong importance/meference
9 Extreme importance/preference
2,4,6,8 Intermediate values between the two adjacent
judgments
If criterion x has one of the above nonzero
Reciprocals of above nonzero numbers assigned to it when compared to y,
then y has the reciprocal value when compared
with x.

 

 

Mollection Method

In this study, pairwise comparison judgments for step one and two were collected using a
12-page written survey instrument, developed with expert stakeholder input obtained
through the in-depth, semi-structured interviews. The survey was mailed to the original
set of 13 experts plus an additional 98 individuals, who were selected using the snowball
sample selection strategy. The selection of these additional interviewees was based on
the recommendations of the original group of experts based on their background and

level of expertise in the issue of mercury emissions from coal-fired power plants.

41

The survey was divided into three sections. In the first section (Section A), the
respondents were asked to rank the six alternative strategies for reducing mercury
emissions from coal-fired power plants, which were identified during the interview
phase. Section B asked the respondents to judge a series of paired comparisons to
indicate the criteria, also identified during the interview process, they believe to be the
most important with respect to the overall goal. This was done to determine the relative
importance the respondents place on each criterion with respect the overall goal. The last
section (Section C) asked the respondents to judge a series of paired comparisons to
indicate their strategy preferences with respect to each of the nine criteria. This process

resulted in a final preference rating for each strategy based on each criterion.

Terms used to describe the evaluation criteria and reduction strategies were carefully
selected and well defined. A table of criteria definitions preceded section B and each
criterion was defined on its respective evaluation table. Carefully and thoroughly
defining each decision element is extremely important in evaluating the hierarchy. Terms
can easily be interpreted differently by different individuals, particular when they
represent diverse interests. Every effort was made to promote consistency across survey

recipient term interpretation in the survey design.

The written survey was distributed to a representative from each of the three survey
groups for pre—testing. Feedback was positive and only one request was made for change.

One reviewer thought that the evaluation criteria and reduction alternative definitions

 

2 Pairwise comparisons can be made in temrs of preference and importance. hnportance comparisons are appropriate when comparing
one criterion with another and preference comparisons are appropriate when comparing alternatives with respect to each criterion.

42

were not clear. In response, the researcher added more detail to each definition to ensure

the decision elements were clearly understood and consistent across all survey recipients.

Responses were solicited from a total of 98 individuals in the three stakeholder groups
(38 environmental staff, 25 regulators, and 35 industry). A consent form was attached to
the front of the survey, which indicated that participation was voluntary and that their
identity and responses would be kept confidential. The written survey instrument was
distributed through US. mail. To ensure a high response rate, a pre-survey e-mail and

post-survey postcard were sent, responses were tracked closely, and various follow-up

methods used.

Step Two: Relative Weight and Preference Calculation

All of the survey responses were entered into a computer implementation of the AHP
called Expert Choice. The numbers derived from the comparisons made in the survey
were used to calculate the weighting vector that yields the relative importance/preference
of each of the decision elements. Although Expert Choice automatically extracts the
relative criterion importance as well as preferences for each strategy, it is important to
understand the mathematical process behind its results. For a more detailed explanation

of the calculations behind AHP, refer to Saaty 1980.

The input data for the decision problem consist of matrices of pairwise comparisons of

elements of one level that contribute to achieving the next higher level. The hierarchy

created for the decision problem in this study has three levels. Level one contains the goal

43

(reducing mercury emissions from coal-fired power plants to target levels), level two
consists of evaluation criteria (determined by stakeholders), and the alternatives
constitute the last level (determined by Stakeholders). First, the evaluation criteria are
compared to each other in terms of relative importance with respect to the goal. Using the
scale in Table l, judgments are elicited from the survey recipients and inserted into the
appropriate matrix cell. If the element on the left is more important than that on the top of
the matrix, one of the values from Table l is entered, depending on the level of
importance. If the opposite is true, the reciprocal value is inserted. Elements compared

against themselves always result in a value of 1.

Table 2: Pairwise comparison matrix for level 2

   

Criteria ('olor \lilcs/(irrllon \VeiUlrtinU \ cctor
h h

   

 

 

 

 

 

 

 

Size 1 1/3 9 .501
Color 3 l 5 .436
Miles/Gallon 1/9 1/5 1 .064

 

 

In the example depicted in Table 2, Size is moderately more important than Color and
extremely more important than Miles/Gallon, etc. These judgments now must be
translated into meaningful numbers that reflect the weight of each criterion with respect
to achieving the overall goal. To obtain this weight, the values in each row are added and
then divided by the sum of all the judgments, or the judgments in any column are simply
normalized (by dividing each entry by the sum of the entries in that column). This

calculation yields the relative importance of the criteria, measured on a ratio scale.

Next, priorities of the alternatives with respect to each criterion are determined using the

same method. The alternatives on the last level of the hierarchy are pairwise compared to

44

each other in terms of preference with respect to the criteria on the next higher level.
Using the scale in table 1, judgments are elicited from the survey recipients and inserted

into the appropriate matrix cell, as illustrated in Table 3.

Table 3: Pairwise comparison matrices for alternative priorities with respect to each
criterion

 

 

Honda Ford Alternative Priority
Ratings
Honda 1/9 3 .250
Ford 1/3 9 .750

 

 

 

 

 

 

Color Ilonda Alternative Priority

 

Ratings
Honda 5 l .833
Ford 1 1/5 .167

 

 

 

 

 

 

 

 

 

\liles/(iallon Honda Alternative Priority
Ratings
Honda 7 3 .955
Ford 1/3 1/7 .045

 

 

 

 

 

 

Step Three: Synthesis

Data synthesis is the third step of the hierarchy evaluation phase. Synthesis is the process
of weighting and combining priorities throughout the model after judgments are made to
yield the final result. The process evaluates how each of the mercury emissions reduction
strategies satisfies the overall goal of reducing mercury emissions from coal-fired power

plants.

Using the priority ratings and the weighting vectors calculated in step three, the mercury

emissions reduction strategy priorities are developed by inserting the priority values of

45

the alternatives with respect to each criterion into the matrix, multiplying each column of
priority vectors by the priority of the corresponding criterion, and then adding across each
row. The highest rated alternative is the one that best meets the evaluation criteria, which

in Table 4 is Honda.

Table 4: Synthesized priorities

 

 

Size Color Miles/Gallon ()Vcrall Priorities
(.501) ( .436) (.064)
Honda .250 .833 .955 .560
Ford .750 . 167 .045 .450

 

 

 

 

 

 

 

Step 4: Sensitivity Analysis

To further analyze the data collected, a sensitivity analysis was performed to investigate
the sensitivity of the alternatives to changes in the priorities of the objectives. This type
of analysis shows the sensitivity of the alternatives with respect to all the objectives
below the goal, as well as the sensitivity of the alternatives with respect to an objective or
sub-objective. Sensitivity analysis is useful because it allows the researcher to vary
priorities of the objectives to observe how the priorities of the alternatives change.
Performing "what-if" sensitivity analyses determines how a change in the importance of
an objective would affect the alternatives of choice. Expert Choice also synthesizes or
combines the priorities that are derived for each facet of a problem to obtain the overall
priorities of given alternatives, as well as how a change in the importance of an objective

affects the alternatives of choice.

46

ETHICAL CONSIDERATIONS

Every researcher, legally and ethically, has an obligation to respect the rights, needs,
values and desires of the informant(s) (Creswell, 1994). This is of particular concern in
this study where some of the informant’s positions and places of employment are highly

visible, and sensitive, job-jeopardizing opinions may be solicited.

In this study, every effort was be made to protect the rights of the respondents, including
informed consent and guaranteed confidentiality. In addition to University Committee on
Research Involving Human Subjects approval, the following safeguards were employed
to respect the subject’s rights. For the in-depth interviews that were conducted to shape
the design of the decision hierarch, subjects were provided (verbally and in writing):
1. A summary explanation of the research, its objectives, purpose, and use of
data.
2. An estimate of the total amount of time required on the part of the subject
(number of sessions, frequency of testing, etc.).
3. Notice that their participation was voluntary.
4. Assurance of confidentiality and anonymity to the maximum extent possible .
5. Disclosure of all data collection devices and activities.
6. Instructions on whom (name and phone number) to contact regarding any
questions or concerns that may be raised by participating in the study, as well

as contact information for the IRB.

47

The interviewees were asked to Sign and return the letter that provided them with the
above information in a postage-paid return envelope (provided), indicating their consent

to participate (see Appendix II).

A similar procedure was followed for the written survey, although written consent to
participate was not requested from the respondents. Complete anonymity was determined
necessary to guarantee an adequate response rate because of the political volatile nature
of the research study topic. Consent was requested instead in a letter attached to the front
of the survey instrument that included the statement: "You indicate your voluntary

agreement to participate by completing and returning this questionnaire." (see Appendix

III).

48

CHAPTER 4
DATA PRESENTATION AND ANALYSIS

This chapter presents the analysis of the data collected from the in-depth, semi-structured
telephone interviews and the written survey instrument. These data were used to develop
and utilize a multi-criteria decision framework to evaluate alternative strategies for
reducing coal-fired power plant mercury emissions. This process included the use of the

AHP software Expert Choice.

HIERARCHICAL DESIGN

As discussed earlier, a literature review was first conducted to develop a list of current
mercury reduction strategies. This tentative list was then incorporated into an interview
guide used to conduct 13 in-depth, semi-structured interviewees with experts from three
different stakeholder groups. These interviews yielded more substantive information
regarding the most preferred mercury strategies for coal-fired power plants as well as the

criteria that Should be used in selecting a strategy.

Utility Industry Interview Responses

Interview responses regarding strategy evaluation criteria varied across the three
stakeholder groups. The four utility industry interviewees favor a strategy that is gradual
and phased to ensure economic feasibility and avoid compromising business viability and

energy reliability. The strategy must allow both for modifications based on new science

49

and compliance flexibility so that each plant operator has latitude in selecting which
reduction method works best. In addition, the strategy should undergo benefit-cost
analysis to ensure that the benefits achieved warrant the cost and are attained at the least
cost. Planning certainty was also mentioned, which mostly centered on the interviewees’
desire to have Congress develop a multi-pollutant strategy so that regulations for all key

pollutants (i.e., NO,, 802, C02, and Hg) are developed simultaneously.

The criterion of paramount importance when selecting a strategy to reduce mercury
emissions from coal-fired power plants, according to the utility industry interviewees, is
scientific defensibility. In fact, those surveyed are not convinced that emission reductions

are even warranted because of critical gaps in scientific research.

One issue the industry respondents identified is understanding mercury cycling and
transformation through air and water on a global and regional scale to determine what
impact changes in mercury source emissions would have on receiving waters and fish.
The interviewees believe that this is important for discussions about strategies for
managing mercury since the results of any management strategy Should be clear and
demonstrable health benefits. For example, one interviewee mentioned research
conducted by a utility research organization that indicates, of the 2,300 metric tons
released annually by human activities around the world, only 2 percent is attributable to
US. coal-fired power plants. If this is the case, said another interviewee, then mercury
emission reductions from US. power plants are not necessary because the reductions will

not result in improvements in US. ecosystems.

50

 

Another unanswered question to which the interviewees pointed involves source
attribution. According to them, there is currently no strong scientific evidence tying the
mercury found in particular waterways and resident fish to particular sources and source
categories. A major obstacle to identifying source contributions is not knowing the
impact of background mercury on mercury concentrations and deposition rates’. Without
this information, the interviewees agreed, it is impossible to effectively reduce mercury

emissions because it is unclear which sources should be controlled.

Because of the scientific uncertainty that surrounds this issue, the utility interviewees
believe that mercury regulation determinations should be put on hold until the above
questions are answered. This will likely not occur for four or five more years, one
interviewee said, which is something that the environmental community will not tolerate.
All four of the interviewees indicated that the environmental community has neither the
scientific background nor expertise necessary to participate in a helpful way to this
debate. One interviewee stated that environmentalists are involved in the mercury issue
not only because they want to reduce mercury exposure, but they also want to eliminate
coal as a fuel source entirely. According to the utility experts interviewed,
environmentalists’ lack of scientific research on the issue combined with their agenda to
eliminate coal often results in unrealistic, unreasonable, and unscientifically based

proposals.

 

’ Background mercury is already present in natural systems and continues to be mobilized in the environment. It is either a naturally
occuning component of soil, water, and plants or a legacy of human activities like mining.

51

ll

A criterion related to scientific defensibility is cost-benefit, which was also discussed as
having strong importance when evaluating mercury reduction strategies. In order to
measure the benefit of a reduction strategy, and then to compare it to the cost of strategy
implementation, the interviewees said, it is important to understand the scientific aspects

of mercury fate and transport and its impact on health.

During the interviews, each person was asked to identify what they viewed as their
preferred strategy for mercury emissions reduction. The main mercury errrission
reduction strategy offered by the utility industry interviewees is a receptor-based strategy,
which would involve setting numerical emission limits for single plants based on their
specific and quantifiable pollution contribution. Most noted that this is not possible
because of scientific constraints. The interviewees also mentioned a multi-pollutant
approach, where multiple pollutants would be regulated at one time. Additionally, the
industry interviewees favored a nationwide emission cap, which would be met by
allowing compliance flexibility across the industry. Emission credit trading was offered
as a way to meet the emission cap. Once the target was met, a residual-risk approach
would follow to address remaining health risks. One strategy that was not favored among
utility industry interviewees was one that prescribed specific control technologies as

compliance flexibility is very important to the industry.

Environmental Group Interview Responses
According to the four environmental group representatives interviewed, there is adequate

scientific evidence that the mercury emitted from coal-fired power plants in the US.

poses a serious health risk to humans and wildlife. The respondents are aware that the
utility industry is not comfortable with the scientific evidence and that not all of the
knowledge gaps have been addressed, but they believe this is not an excuse to do nothing.
One interviewee stated that the precautionary principle Should be applied in this Situation
because providing too much protection of public health is preferred over not being

protective enough.

The environmentalists favor a mercury reduction strategy that is effective in protecting
public health and provides the utility industry with planning certainty. They also desire a
strategy that is cost-effective by producing multiple pollution reduction benefits. The
environmental respondents require the strategy to be legally defensible and politically

feasible to avoid stalling action by industry.

The environmental interviewees prefer the multiple pollutant and numerical emissions
cap reduction strategies, although they do not prefer using mercury emission trading to
meet the cap and have already developed a target reduction percentage to calculate the
cap (90%). The environmentalists agree that compliance flexibility is important, but
believe that the strategy could include prescriptive reduction options including a
renewable resource portfolio standard and the inclusion of energy conservation and
energy efficiency programs/practices. Installing emission control technology was also
mentioned as a way to meet the cap, but only if the removed mercury is properly
disposed of to ensure it is not just being removed from one media (air) to be placed in

another (soil, water, etc). One respondent suggested issuing an ambient deposition

53

standard for mercury Similar to standards set for criteria pollutants, admitting this would

be difficult to monitor and enforce.

Government Agency Interview Responses

Interviews were conducted with five government agency representatives. Responses
varied considerably depending on the agency, department, and area of specialization the
interviewee represented. The opinions of those whose work involves the development of
regulations and working directly with Congress are much different from those who are
more involved with researching, developing, and demonstrating air pollution prevention

and control for power plants.

Those working in regulatory development favor a strategy that is “fair” to the utility
industry in that it allows for compliance flexibility to optimize pollution reductions in a
cost-effective way and planning certainty so that plant owners and operators are aware of
future technology needs and, therefore, can make informed pollution abatement choices.
These individuals also believe political feasibility is important because a lack of political
support means a slow-down in the regulatory development process. They do not want a
strategy put forward that is politically uncertain because it may result in lawsuits, etc.,
that stall action. Interviewees also believe the criteria listed in the Clean Air Act, which
they are bound to apply in evaluating different mercury control strategies, are important.
In terms of preferred reduction strategies, this set of interviewees favor the multi-

pollutant approach because it provides the industry a degree of planning certainty.

54

The other set of government agency interviewees, who are involved with researching and
developing pollution abatement technology, approach this topic from a purely scientific
standpoint. Scientific defensibility is very important to these individuals when evaluating
a reduction strategy, as is cost-benefit. Arguments Similar to those of the utility industry
were made regarding mercury fate and transport and actual vs. perceived health risks.
This indicates that these interviewees are approaching this mercury regulatory issue from

a similar viewpoint.

Hierarchical Structure Design
After the interviews were complete, the list of the most prominent mercury reduction
strategies and evaluation criteria identified by the interviewees was arranged into a

decision hierarchy. Figure 4 shows the final AHP tree.

At the top of the tree is the overall goal, identified by the researcher, of reducing mercury
emissions from coal-fired power plants to target levels. On the next level, nine criteria are
identified as essential for achieving the overall goal: effectiveness, economic feasibility,
technological feasibility, compliance flexibility, planning certainty, political feasibility,
scientific defensibility, legal feasibility, and cost vs. benefit. The criteria are defined as
follows:

0 Effectiveness: the ability of the reduction strategy to achieve the goal of reducing

mercury emissions to target levels

55

Figure 4: AHP decision hierarchy for identifying an optimal strategy to reduce
mercury emissions from coal-fired power plants

 

 

 

GOAL: To reduce mercury
emissions from coal-fired

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

power plants
CRITERIA
Effectiveness Economic Planning Political Cost -
\ Feasibility Certainty Feasibility Benefit
Technological Compliance Scientific Legal

Feasibility N Flexibility Defensibility y Feasibility

w

ALTERNATIVES

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MACT MACT numerical Receptor-based
numerical emission limit plus emissions limit
emission limit emissions trading

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MACT Multi- Risk-based
technology pollutant ' emissions
regulation regulation limits

 

 

 

 

 

 

 

 

 

 

56

 

0 Economic feasibility: the impact that reduction strategy implementation will have
on business viability and power reliability

0 Technological feasibility: the need for new technology to implement the strategy

0 Compliance flexibility: the amount of industry latitude the reduction strategy
allows in selecting a reduction method] technology

0 Planning certainty: the level of certainty the reduction strategy provides the utility
industry regarding future pollutant regulations and pollution control needs

0 Political feasibility: the level of existing political constraints in implementing the
reduction strategy

0 Scientific defensibility: the associated level of scientific certainty justifying the
need for the reduction Strategy

0 Legal feasibility: the need for new or modified laws to implement the strategy

0 Cost-benefit: the degree of benefit in terms of mercury emission reductions and
associated environmental and health benefits compared to the cost of

implementing the strategy

The mercury reduction strategies are presented at the bottom of the tree. The strategies
mentioned most often during the interviews and, therefore, included in the decision tree

are:

0 Maximum Achievable Control Technology (MACT) numerical emission limit:
EPA determines MACT emissions limit and leaves the choice of control

technology to the utility industry.

57

o MACT technology regulation: EPA determines MACT emissions limit and
promulgates a technology standard for the utility industry.

0 MACT numerical emission limit plus emissions trading: EPA determines MACT
emissions limit and leaves the strategy for compliance up to the utility industry
including emissions trading.

0 Multi-pollutant regulation: EPA establishes and promulgates emission standards
for multiple pollutants (e.g. NOx, C02, 802, and Hg) at one time.

0 Receptor-based errrissions limits: EPA establishes and promulgates mercury
emission standards for single plants based on their specific and identified
pollution contributions.

0 Risk-based emissions limit: EPA establishes and promulgates a mercury emission
standard for the utility industry based on risk to human health and the

environment.

HIERARCHY EVALUATION
The second phase of the AHP is the evaluation of the hierarchy, which is a four step
process:
1) Collecting input data (judgments) by pairwise comparisons of the decision
elements,
2) Calculating relative weights and priorities of the decision elements to
determine priorities,
3) Synthesizing the relative weights and priorities to determine the best

dmeWQ

58

Survey Response Rate

A written survey was sent to 98 Stakeholders, who were asked to evaluate a series of
paired comparisons regarding the identified criteria and mercury reduction strategies. Of
the 98 surveys distributed, 35 were mailed to utility industry and research organization
representatives, 38 were mailed to environmental organization representatives, and 25
were mailed to government agency representatives. The survey instrument used can be

viewed in Appendix IV.

Table 5: Survey response rates by stakeholder group

 

 

 

Utility Industry 35 17 49
Environmental Org. 38 12* 32
Government Agency 25 8 32
Total individuals 98 37 38

 

 

 

 

 

 

*One survey was returned incomplete and. therefore, not counted here.

The response rates with respect to each stakeholder are summarized in Table 5. Overall,
more than 1/3 of the recipients returned usable surveys. The response rate was the highest
for the utility industry stakeholder group. Considering the length of the survey and the
tense political environment created by the recent EPA positive mercury regulatory

determination, this was considered a good response.

Criteria Weight and Strategy Preference Results

One of the major strengths of AHP is the use of pairwise comparisons to derive accurate
ratio scale priorities, instead of using traditional approaches of ‘assigning’ weights. This
process compares the relative importance of two elements (e. g., strategy evaluation

criteria) with respect to another element in the level above (e.g., the goal of reducing

59

process compares the relative importance of two elements (e.g., strategy evaluation
criteria) with respect to another element in the level above (e.g., the goal of reducing
mercury). A judgment is made for each pair as to which is more important and by how

much.

In this study, a written survey instrument was used to elicit from respondents the
importance weights of the nine evaluation criteria and the six reduction Strategies for

reducing mercury emissions from coal-fired power plants.

Criteria Importance Weighting
Survey participants were asked to compare the relative importance they place on each
evaluation criterion when selecting a strategy to reduce mercury emissions from coal-
fired power plants. To minimize the demands on respondents and thereby hopefully
increase the survey response rate, a diagonal paired comparison approach was used. This
allows the minimum number of comparisons necessary to calculate all the priorities. The
following 8 paired comparisons were made by all respondents:

' Effectiveness versus Economic feasibility.

' Economic feasibility versus technological feasibility.

. Technological feasibility versus compliance flexibility.

I Compliance flexibility versus planning certainty.

' Planning certainty versus political feasibility.

' Political feasibility versus scientific defensibility.

' Scientific defensibility versus legal feasibility.

6O

On the basis of these eight comparisons the remaining paired comparisons could be
extrapolated. The average relative importance or priority weights of the criteria were
analyzed by Stakeholder group (see Table 6 and Figure 5). For each group, the priority

weights for the criteria add up to one.

Table 6: Criteria weights for each stakeholder group

Effectiveness
Economic
T

Political
Scientific

Cost-benefit . . .184
Total . . 1.000

 

Utility Industry Responses

The strongest relative criteria importance weights were observed for the utility industry
stakeholder group. To reduce mercury emissions to target levels, the utility industry
Stakeholder group believes that cost—benefit (.266) and scientific defensibility (.248) are
far more important than any of the other criteria. These criteria weights are more than

double that of the next most important criterion, compliance flexibility (.119).

These results are not surprising, as the in-depth interview responses revealed the same

conclusions. Interviewees consistently indicated that a high of level scientific evidence

justifying the need for a certain reduction strategy is very important to them. In addition,

61

 

 

 

 

2‘ 730) >
‘55 E5 0 l
3 “3:: g I
'0 Em C,
5 CE <
O:
2‘ has 3*
= >0) >
'4: Ch 0
D 1110 (D
I E]
l L J

 

 

 

 

 

 

 

  

 

 

 

Figure 5: Comparison of evaluation criteria weights

 

 

 

 

 

 

0.30

l R\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\‘~ °>
l .
w 09,
i R\\\\\\\\\\\\\\ ago
. l ’ ° 0
l I 962’s
l l l 14:0,
. l\ 60 its,
l L I
‘3 ‘3 S
rufirom

62

 

Evaluation Criteria

interviewees repeatedly suggested that the evaluation of the degree of benefit (in terms of
mercury emission reductions and associated environmental and health benefits) compared

to the cost of implementing a reduction strategy is an important factor to consider.

The least important evaluation criteria, according to the utility responses, are
effectiveness, i.e. the ability of the reduction strategy to reduce mercury to target levels,
and technological feasibility, i.e. the need for new technology to implement the reduction
strategy. Both of these criteria have a weighting vector of .041. This suggests that the
utility industry thinks the effectiveness of a strategy or the need for new technology to

implement the chosen strategy is not as important as the other criteria.

Although the effectiveness criterion was not advocated as strongly during the in-depth
interviews as cost-benefit and scientific defensibility, every utility industry representative
interviewed mentioned it as being important. Therefore, it is surprising that it is tied with
technological feasibility as the least important criteria (.041). The low weighting of the
criterion technological feasibility is not surprising, since that criterion was not stressed

often in terms of importance during the interviews.

finvironmenil Organization Resmnses

The environmental group weighted the criteria planning certainty (.197) and legal
feasibility (.195) as more important relative to the other criteria. The fact that
environmentalists believe it is important to consider the level of legal constraints that

exist for different reduction strategies when choosing between them is not unexpected,

63

since the individuals interviewed are primarily policy advocates whose focus is
modifying laws and regulations. The high weight given to planning certainty, on the
other hand, is unexpected. This result suggests that the environmental community
believes the most important evaluation criterion is the extent to which a strategy provides
the utility industry with certainty regarding future pollutant regulations and pollution
control needs so that appropriate investments and design decisions can be made
effectively and efficiently. Although it was mentioned during the interviews, it was not

evident that this criterion was of such importance to this group.

Scientific defensibility is also relatively important to this stakeholder group, receiving a
weighting vector of .177. This result is not surprising because many of the
environmentalists interviewed stressed the importance of a scientifically valid strategy
and believe that the level of existing evidence is adequate to warrant regulation. The
utility industry also weighted this criterion very high, in fact the interviewees’ biggest
complaint regarding the mercury regulatory determination is the lack of scientific
evidence demonstrating its need. Although both stakeholder groups agree that this is an
important factor, it appears that their definition of scientific defensibility differs since one
group believes that there is currently adequate science to warrant mercury regulations and

the other does not.

Of least relative importance to the environmental survey group is economic feasibility.

This suggests that the impact the reduction strategy will have on power company

business viability and customer power reliability is not as important an evaluation

64

criterion. This is not surprising considering many environmentalists indicated that they

believe the utility industry often exaggerates the potential cost of regulatory compliance.

Government Agencv Responses

The government agency respondents weighted the evaluation criteria more evenly than
either of the other two groups (i.e. low of .064 and a high of .184). A weight of .184 is
given to the cost-benefit criteria, followed closely by scientific defensibility (.165), and
compliance flexibility (.161). All three of these criteria were also mentioned repeatedly
during the in—depth interviews. The remaining criteria were weighted relatively equally,
with weighting vectors between .114 and .064. These survey results suggest that cost-
benefit, scientific defensibility, and compliance flexibility are slightly more important
than the other evaluation criteria considered, but the agency survey group weights all the

evaluation criteria relatively equally.

It is not surprising that strong importance weights were not given for any of the criteria
because most of those interviewed did not strongly advocate for any criterion in
particular. It was expressed several times during the in-depth interviews with some
individuals from the government agency stakeholder group that their role is to follow the
mandates prescribed in the Clean Air Act and that maintaining and advocating particular
opinions regarding either evaluation criteria or preferred reduction strategies is
inappropriate. Although it was explained to these interviewees that the experience they
have with the issue gives them an extremely valuable opinion, those interviewed were

still reluctant to express personal judgments.

65

It is interesting to note that both the utility industry and the government agency
respondents selected the same criteria as their top three most important evaluation
criteria. For both groups, cost-benefit was the most important decision criterion,

followed by scientific defensibility and compliance flexibility.

Paired Comparisons of Mercury Strategies

Having determined the relative importance of the nine evaluation criteria, the next step in
the AHP is to relate these criteria to the mercury reduction strategies. The survey
respondents were asked to use the same 1 (equal importance) through 9 (extreme
importance) scale and make paired comparisons between mercury reduction strategies to
indicate their level of relative preference with respect to each of the nine different
evaluation criterion. Each respondent was required to make 53 pairwise comparisons (see

Appendix 1V).

Utility Indusgy Resmnses

The utility industry’s pairwise comparison strategy preference results with respect to each
criterion are depicted in Figure 6. In terms of effectiveness, the most preferred strategy
is the risk-based emissions limit, receiving an overall preference rating of .374, followed
by the multi-pollutant regulation strategy (.223), MACT numerical emissions standard
plus trading (.149), MACT numerical emissions standard (.127), receptor-based

emissions standard (.097), and MACT technology standard (.031).

66

Figure 6: Utility Industry paired comparison results

 

I Risk-Based

E Receptor-Based

El Multi-Pollutant

5 Numerical +Tradlng
E] MACT Tech

E Numerical Standard

 

 

 

 

w-llllllllllllllll7/%

     
  
 
   
   
   
 

  

— a...
N-llllllllllllllllllllllll-W @ e
_ *9»,
, , m-umlnmlle , ’42.,
”IIIIIllllllllllllll-W 99°99.

  

e‘“
09
Q
9.?

Evaluation Criteria

  

~_|I|||||lllllllllllillll%///////, e “9%
. i 1%
r . l ‘b
t , o
§\-ll||||||l|||llllllllllllllllllIW @ ‘90.,
/9+
k\\-IlllllllllllllllllllllI% 1,, ’ o
09%
N_lllllllllllllllllllIV///A 1,, “9.»
[/9099 [0"69
’0 0°
“3% IQOOO (
Tooootsoo”; “a?"
§22223§2232 99.,

uwuerts eoueieierd

67

With respect to economic feasibility, the risk-based emissions strategy again is the most
preferred, receiving an overall preference rating of .372. The next most preferred strategy
is the multi-pollutant regulation strategy at .240, MACT numerical emissions standard
plus trading at .152, MACT numerical emissions standard at .107, receptor-based

emissions standard at .105, and MACT technology standard at .024.

The risk-based emissions standard is most favored in terms of technologic feasibility, as
well, receiving a .376 preference rating. The next most preferred strategy is the multi-
pollutant regulation strategy (.196), followed by the MACT numerical emissions
standard plus emissions credit trading (.173), receptor-based emissions standard (.110),

MACT numerical emissions standard (.100), and MACT technology standard (.045).

In temrs of compliance flexibility, the utility industry still prefers the risk-based
emissions standard at .282, although the MACT numerical emissions standard plus
emissions credit trading strategy advances considerably (.237). The multi-pollutant
regulation strategy is next in the preference rank at .196, followed by the MACT
numerical emissions standard at .167, receptor-based emissions standard at .082, and

MACT technology standard at .036.

With respect to planning certainty, the multi-pollutant approach is the most favored
reduction strategy (.249), but not much more preferred than the risk-based emissions
standard (.221). The next most preferred strategy is the MACT numerical emissions

standard plus emissions credit trading (.174), followed by the MACT numerical

68

emissions standard (.142), receptor-based emissions standard (.130) and MACT

technology standard (.084).

In terms of political feasibility, the MACT numerical emissions standard is preferred
over the other strategies, with a preference weight of .308. The multi-pollutant regulation
strategy follows distantly at .198, as do the MACT numerical emissions standard plus
emissions credit trading (.155), risk-based emissions standard (.130), MACT technology

standard (.125), and the receptor-based emissions standard (.084).

With respect to scientific defensibility, the utility industry prefers the risk-based
emissions standard (.545) four times more than the next most preferred strategy, the
receptor-based emissions standard (.133). The multi-pollutant regulation strategy is next
in the preference rank with a weight of .124, followed by the MACT numerical
emissions standard plus emissions credit trading (.095), MACT numerical emissions

standard (.065), and MACT technology standard (.037).

None of the reduction strategies are preferred strongly over the others in terms of legal
feasibility. The risk-based emissions standard (.215) is preferred slightly more than the
MACT numerical emissions standard (.199), followed by the MACT numerical
emissions standard plus emissions credit trading (.191), multi-pollutant regulation
strategy (.147), MACT technology standard (.139), and receptor-based emissions

standard (.109).

69

The utility industry expresses a strong preference for the risk-based emissions standard
(.481) in terms of cost benefit analysis, which is favored almost three times more than
the next most preferred strategy, the multi-pollutant regulation strategy (.170). The next
most preferred strategies are the MACT numerical emissions standard plus emissions
credit trading (.118), receptor-based emissions standard (.114), MACT numerical

emissions standard (.097), and the MACT technology standard (.019).

In summary, the risk-based reduction strategy is the most favored among utility industry
survey respondents in terms of (in order of preference strength) scientific defensibility
(.545), cost-benefit (.418), technological feasibility (.376), effectiveness (.374),
economic feasibility (.372), compliance flexibility (.282), and legal feasibility (.215).
The only criteria for which the risk—based standard does not rank highest are political
feasibility and planning certainty. With respect to political feasibility, the utility industry
prefers the MACT numerical emission limit (.308) and in terms of planning certainty, the

group favors the multi-pollutant strategy (.249).

Environmental Organization Responses

Figure 7 shows the environmental organization’s pairwise comparison strategy
preference results with respect to each criterion. With respect to the effectiveness
evaluation criterion, the environmental organization stakeholder group has a strong
preference for the multi-pollutant regulation strategy (.384) and the MACT numerical
emissions standard (.306). These strategies are followed distantly by the MACT

technology standard (.112), risk-

70

Figure 7: Environmental organization group paired comparison results

 

 

fi Numerical Standard J

E! Multi-Pollutant
I MACT Tech

 

 

 

1.001

i

i i
§

1

i
r
a
O

i
%
o
m.
0

 

* a Receptor-Based

-- 5 Numerical +Trading

 

 

(

-

 
 
    

HHIIIH e

I 1
l

 

    
 

i

 

 

J illIllllllllHlHlHlHlllll//////////// , “3%

 

 

\\V

 

mum V//////// ., “9%

 

 

 

 

i

 

 

i HIHIHHHIIUIU *2.
l

 

 

 

llillllilllll
‘ ,

 

 

 

 

i
1

 

0 60
050 he“
0.40 -

0 30

0 20 J

‘3. 8 <9
0 O

utfiuens eoumeieid

7l

 

Evaluation Criteria

based emissions standard (.078), receptor-based emissions standard (.062), and MACT

numerical emissions standard plus emissions credit trading (.057).

The strength of the preference for the multi-pollutant regulation strategy (.443) is even
stronger with regard to economic feasibility, which is preferred twice as much as the
next most preferred strategy, the MACT numerical emissions standard (.206). The
MACT numerical emissions standard plus trading and risk-based emissions standard are
less preferred, each receiving a preference ranking of .119. The least preferred strategies
are the receptor-based emissions standard (.069) and the MACT technology standard

(.045).

Both the MACT numerical emissions standard and the multi-pollutant regulation strategy
are preferred significantly to the other strategies with respect to technological feasibility,
receiving .349 and .297 preference ratings, respectively. These strategies are followed in
the preference ranking by the MACT numerical emissions standard plus emissions credit
trading (.106), MACT technology standard (.102), risk-based emissions standard (.085),

receptor-based emissions standard (.060)

In terms of compliance flexibility, the environmental organizations surveyed prefer the
multi-pollutant regulation strategy (.347) and the MACT numerical emissions standard
(.271). Less preferred are the MACT numerical emissions standard plus emissions credit
trading (.151), risk-based emissions standard (.112), receptor-based emissions standard

(.068), and MACT technology standard (.052).

72

With respect to planning certainty, the multi-pollutant regulation strategy is preferred
twice as much (.403) as the MACT numerical emissions standard (.201). The next most
preferred reduction strategy is the MACT technology standard (.116), risk-based
emissions standard (.102), receptor-based emissions standard (.098), and lastly the

MACI’ numerical emissions standard plus emissions credit trading (.080).

According to the environmental organization stakeholder group, the most politically
feasible strategies are the multi-pollutant regulation strategy (.277), the MACT numerical
emissions standard (.240) and the MACT numerical emissions standard plus emissions
credit trading (.222). The strategies that are less preferred in terms of political feasibility
are the risk-based emissions standard (.108), MACT technology standard (.085), and

receptor-based emissions standard (.069).

The multi-pollutant regulation strategy is preferred the most in terms of scientific
defensibility with a preference level of .317. Following distantly in terms of preference
are the MACT numerical emissions standard at .190, risk-based emissions standard at
.185, MACT technology standard at .42, receptor-based emissions standard at .098, and

MACT numerical emissions standard plus emissions credit trading at .068.

With respect to legal feasibility, the survey results reveal a strong preference for the

MACT numerical emissions standard (.334) and the MACT technology standard (.250).

The least preferred strategy in terms of legal feasibility are the multi-pollutant regulation

73

strategy (.143), risk-based emissions standard (.118), MACT numerical emissions
standard plus emissions credit trading (.081), and receptor-based emissions standard

(.074).

The strongest preference observed for any strategy is for the multi-pollutant regulation
with respect to cost vs. benefit. Its preference rating is .500, followed distantly by the
MACT numerical emissions standard at .165, risk-based emissions standard at.122,
MACT numerical emissions standard plus emissions credit trading at .084, receptor-

based emissions standard at .066, and the MACT technology standard at .063.

Overall, the environmental group respondents prefer the multi-pollutant strategy with
respect to cost-benefit (.500), economic feasibility (.443), planning certainty (.403),
effectiveness (.384), compliance flexibility (.347), scientific defensibility (.317), and
political feasibility (.277). The only evaluation criteria that the multi-pollutant strategy
did not satisfy were legal feasibility (.143) and technological feasibility (.067). The
MACT numerical standard is preferred the most with respect to those criteria (.334 and

.349 respectively).

Government Agency Resmnses

Figure 8 shows the government agency’s pairwise comparison strategy preference results
with respect to each criterion. In terms of effectiveness, the government agency survey
group prefers the multi-pollutant regulation strategy (.300), followed closely in the

preference ranking by the MACT numerical emissions standard at .272. The least

74

 

 

Emecmfi .motmEzz a
com... .552 a
9:69.: _mo:mE:z m
EmS=on_-_=2>_ D
eommmaofimoom E

nmmmm-xm_m I

 

stoic coeuagm

.33.“. - ! . . .

u e... r. ... ..

. Inc-w)» m...» it: u .m- fid $.an
- .

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3.33. couteoEoo vogue >239 EoEEo>oG 6 0.52“.

 

 

 

 

 

- 8.0
L. Ed

o3

i. r and

ii, and

[T and

 

# and

if cad

 

. 8.—

114619,“ eoueieieid

75

preferred strategies are the MACT numerical emissions standard plus emissions credit
trading with a preference rating of .160, followed by the risk-based emissions standard at

.118, receptor-based emissions standard at .093, and MACT technology standard at .057.

The government agency respondents prefer the multi-pollutant regulation strategy the
most (.277) with respect to technological feasibility, followed closely by the MACT
numerical emissions standard (.249), MACT numerical emissions standard plus
emissions credit trading (.199), receptor-based emissions standard (.117), risk-based

emissions standard (.101), and MACT technology standard (.056).

The MACT numerical emissions standard, MACT numerical emissions standard plus
emissions credit trading, and multi-pollutant regulation are the most preferred strategies
in terms of compliance flexibility, receiving preference ratings of .298, .275, and .210
respectively. The least preferred strategies are the risk-based emissions standard,
receptor-based emissions standard, and MACT technology standard with ratings of .098,

.080, and .047, respectively.

The government agency respondents have a strong preference for the multi-pollutant
regulation strategy (.361) in terms of planning certainty, which is preferred more than
twice as much as the next most preferred strategy: the MACT technology standard (.165).
This strategy is followed closely in terms of preference by the MACT numerical

emissions standard (.146), the MACT numerical emissions standard plus emissions credit

76

trading (.125), the receptor-based emissions standard (.116), and lastly the risk-based

emissions standard (.088).

The MACT numerical emissions standard is the most preferred strategy in terms of
political feasibility by this stakeholder group, receiving a preference rating of .327. The
multi-pollutant regulation and the MACT numerical emissions standard plus emissions
credit trading strategies are the next most preferred strategies, rating .241 and .233
respectively. The least preferred strategies are the MACT technology standard (.078), the

risk-based emissions standard (.063), and the receptor-based emissions standard (.058).

Of the six reduction strategy alternatives, the MACT numerical emissions standard
(.222), multi-pollutant regulation strategy (.217), MACT numerical emissions standard
plus emissions credit trading (.204), and the MACT technology standard (.183) are all
preferred roughly the same in terms of scientific defensibility. The next most preferred
strategy is the receptor-based emissions standard (.111), followed by the risk-based

emissions standard (.063).

The most preferred strategies in terms of legal feasibility are the MACT numerical
emissions standard (.291) and the MACT technology standard (.229). The MACT
numerical emissions standard plus emissions credit trading is given a priority vector of
.155 by the government agency stakeholder group, followed by the multi-pollutant
regulation strategy at .143, receptor-based emissions standard at .095, and risk-based

emissions standard at .087.

77

The multi-pollutant regulation strategy is the most preferred strategy in terms of the
degree of benefit compared to cost. Its preference rating is .335, followed by the MACT
numerical emissions standard plus emissions credit trading (.227), MACT numerical
emissions standard (.203), risk-based emissions standard (.095), receptor-based emissions

standard (.091), and MACT technology standard (.049).

To summarize, the government agency response group prefers the multi-pollutant
strategy with respect to planning certainty (.361), cost-benefit (.335), economic feasibility
(.315), effectiveness (.300), and technological feasibility (.277). In terms of political
feasibility (.327), compliance flexibility (.290), legal feasibility (.291), and scientific

defensibility (.222) the group prefers the MACT numerical standard.

Priority Synthesis Results

The remaining task in the AHP is to synthesize the strategic priorities discussed above
with the evaluation criteria weightings to determine the relative preferences among the
six reduction strategies for each stakeholder group. The tables below present the
preference weights for each of the reduction strategies with respect to each evaluation
criterion for each stakeholder group. See Figure 9 for a graphical comparison of the

synthesized strategy preferences across all three stakeholder groups.

78

Figure 9: Comparison of overall strategy preferences
(numbers above bars represent rank order)

0.450

0.400

       

I Industry
.. ,a Enviro Org

 

_.\

an! r

W

\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\

 

 

8
q
o

0 050
0.000

O O
I!) O
or or
O O

qrfiuens aoueieierd

79

Receptor- Based

a MACT

MACT Numerical Risk-Based MACT Numeric |

Mum-Pollutant

Technology

+ Trading

Strategy

Utility Industry Responses

The synthesis results indicate a strong preference among utility respondents for the
risked-based mercury emissions reduction strategy. The synthesized preference weight
for this strategy is .392, which is more than twice that of the next most preferred strategy,
the multi—pollutant regulation (.176). These are followed by the MACT numerical
emissions standard plus emissions credit trading (.145), MACT numerical emissions
standard (.124), receptor-based emissions standard (.113), and MACT technology
standard (.049). Table 7 provides a summary of the criteria importance weights and the
paired comparison results, which are multiplied and summed across each row to
determine the strategy preferences in the last column. Figure 10 depicts the utility

industry group’s strategy preferences graphically.

Table 7: Utility industry strategy priorities with respect to evaluation criteria and
final preference weights.

Standard

 

80

339.5

9:3:
329.58 F052 ummmmsoaoomm _mo:oE:z ._.o<__2 + _mo:oE:z ._.0<s_ EmS__0n_-=_:_2 vmmmmiwi

, i. omod

 

09.0

 

. omfio

 

oomd

 

. ommd

 

till 0006

 

. ommd

 

 

oovd

 

 

 

omvd

moo—.2205 322$ =u._o>o 9.0.5 Page... 355 now 0.59".

utfiueus eoueieiard
8 1

Environmental Organization Responses

The preferred strategy for the environmental organization stakeholder group is the multi-
pollutant regulation strategy with a preference rating of .324. Next are the MACT
numerical emissions standard (.251), the MACT technology standard (.132), the risk-
based emissions standard (.119), the MACT numerical emissions standard plus emissions
credit trading (.094), and the receptor-based emissions standard (.079). Table 8 provides a
summary of the criteria importance weights and the paired comparison results, which are
multiplied and summed across each row to determine the strategy preferences in the last
column. Figure 11 depicts the environmental organization group’s strategy preferences

graphically.

Table 8: Environmental organization strategy priorities with respect to evaluation
criteria and final preference weights. The importance weights of the evaluation
criteria are given below the titles.

Standard

 

82

>385

use“;
889588.". + 38252 532 8332.". 32858 552 .8852 5,3 €338.23:
t. \V\ Sod
._ . \ .\
89°
83

0mm.0

000.0

 

woo—.239:— 3838 =a._o>o 3.0.6 533.595 .8eoE:o._>cm u: 230E

Government Agency Responses

The synthesis of these priorities yielded no strong preferences. The multi-pollutant
regulation strategy is slightly more preferred (.267) than the MACT numerical emissions
standard (.242) and the MACT numerical emissions standard plus emissions credit
trading strategy (.206). The least preferred strategies are the MACT technology standard
with a preference rating of .097, the receptor-based emissions standard at .097, and the
risk-based emissions standard at .091. Table 9 provides a summary of the criteria
importance weights and the paired comparison results, which are multiplied and summed
across each row to determine the strategy preferences in the last column. Figure 12
depicts the government agency group’s strategy preferences graphically.

Table 9: Government agency strategy priorities with respect to evaluation criteria

and final preference weights. The importance weights of the evaluation criteria are
given below the titles.

 

Standard

Strategy Preference Ranking

The AHP requires that individuals break down the problem into components or elements.

These elements are then rated in terms of relative preferences through a series of pairwise

84

>385

053;
“anemia: oomameofiooom 3205.8... .552 + .3toEaz .552 iota—=32 .552 “Engages:
_ . , . 80.0
omod
09.0

E
0'
mnuens eoueremd

§
0'

find

000.0

 

30:232.". 33:...» =Eo>o 9.20 >0:er «cop—.5260 "Nw 230.".

85

Strategy Preference Ranking

The AHP requires that individuals break down the problem into components or elements.

These elements are then rated in terms of relative preferences through a series of pairwise

comparisons. The preferences are then synthesized to identify the order of preference

among the alternatives. The respondents are never asked directly to identify their relative

preferences among the alternative strategies under consideration.

A question of methodological interest is whether the AHP's deconstruction approach

would yield similar results to the more traditional and simple ranking of alternatives. To

test this, survey respondents were asked to rank the six mercury reduction strategies from

one to six, assigning l to their most preferred strategy and 6 to their least preferred

strategy (see Appendix IV). Table 10 summarizes the strategy preferences generated by

the two approaches for each stakeholder group.

Table 10: Comparison of strategy preferences generated by two approaches (listed
in order of preference, with the most preferred strategy first)

l" ”H l'\ l\l)l S 1 RV

li.\\ ll{()\\lli\ l. \l. ()RU

(i()\ l-.|(.\\llx\ l‘ \(il-_\( '\

 

 

\Hi’

Rankin;

\lil’

Rdliixill‘.‘

\lil’

Rdllixilll'

 

 

 

 

 

 

 

 

 

 

 

Most Risk-based Risk-based Multi-pollutant Multi-poliutant Multi-pollutant Multi-pollutant
Preferred Multi-poliutant Muiti-pollutant Numerical Numerical Numerical N umerical
standard standard standard standard
Numerical + Numerical + MACT Tech MACT Tech Numerical + Numerical 4»
Trading Trading standard standard Trading Trading
Numerical Receptor Risk-based Risk-based MACT Tech MACT Tech
standard based standard standard! Risk-
based (tie)
Receptor based Numerical Numerical 4» Receptor based Receptor based
standard Trim;
1“” MACT Tech MACT Tech Receptor based Numerical + Risk-based Receptor
”Wm" standard standard Trading based

 

86

 

Utility Strategy Ranking

Using the ranking approach, of the 17 utility respondents, 12 rank the risk-based standard
as the most preferred strategy (mean, 1.63; SD, 1.41). Ranking second among the six
strategies is the multi-pollutant regulation (mean, 2.56; SD, 1.55). Ranking third is the
MACT numerical emission limit including emissions credit trading (mean, 3.25; SD.856)
followed closely by the receptor-based emission limit strategy (mean, 3.69; SD, 1.49).
The least preferred strategies are the MACT numerical emission limit (mean, 4.44; SD

1.03) and the MACT technology standard (mean, 5.44; SD, .727).

Both the AHP and ranking approaches produced roughly the same strategy preference
ranking for the utility industry stakeholder group, except with respect to the numerical
emission and the receptor-based strategy rankings. The AHP calculated the numerical
standard as the fourth most preferred strategy, followed by the receptor-based strategy,

while the ranking results conclude the opposite.

Environmental Organization Ranking

When asked to rank the six reduction strategies, the survey respondents from the
environmental stakeholder group almost unanimously select the multi-pollutant emission
reduction strategy as their most preferred alternative (mean, 1.25; SD, .621). Only two
respondents do not believe this is the best strategy, with one ranking it second and the
other ranking it third. The MACT numerical emission standard (mean, 2.67; SD, 1.30)

and the MACT technology emission standard (mean, 2.67; SD, 1.07) are both ranked

87

second, followed by the risk-based emission standard (mean, 3.92; SD, 1.68) and the
receptor -based emission standard (mean, 4.42; SD, 1.08). The least preferred of the six
strategies was the MACT numerical emission standard plus trading (mean, 5.08; SD,

1.34).

Both the AHP and ranking approaches produced the same top three strategy preference
rankings for the environmental group. The two least preferred strategies were different.
The AHP calculated the numerical plus trading and receptor-based strategies as fifth and

sixth in the priority ranking, while the ranking results conclude the opposite.

Government Agency Ranking

It was difficult to determine strategy preferences among the agency respondents because
their responses were not uniform, i.e. responses varied greatly for each strategy. Table 11
illustrates the inconsistencies in survey responses; with the most preferred mean score
being 2.00 (SD 1.77) and the least preferred being 4.88 (SD: 1.80). For example,
according to the mean ranking score, the MACT numerical standard is the second most
preferred reduction strategy among government agency employees surveyed (mean, 2.63;
SD, 1.69), but when the frequency distribution is analyzed, it is clear that the preferences
are widely distributed. Of the total government agency responses, 25 percent rank the
MACT numerical standard as the most preferred strategy, 37.5 percent rank it second,
12.5 percent rank it third, 12.5 percent rank it fourth, and 12.5 percent rank it last. This
kind of distribution decreases the robustness of the strategy preference ranking for this

stakeholder group.

88

Table 11: Government agency group strategy preference ranking
(l=most preferred)

 

 

 

 

 

 

 

 

Numerical .\l.-\ ("F 'l‘cch Numerical Multi- Ret‘eptor- Risk-Based
Standard Standard +Trading Pollutant Based Standard
1 5 3 6 2 4
3 4 2 1 6 5
4 3 2 1 6 5
2 6 3 1 5 4
2 4 1 3 6 5
6 4 3 1 2 5
2 5 3 1 6 4
1 4 5 2 6 3

 

 

 

 

 

 

 

 

Both the AHP and ranking approaches produced the same results for the first, second,
third, and fourth most preferred strategies. The AHP results indicated that the receptor-
based followed by the numerical plus trading strategies were the least preferred, but the
ranking results moved the risk-based standard up along side the MACT technology
standard tied for fourth place in the preference order, followed by the receptor-based
standard. These results infer that the government agency group prefers the risk-based
strategy less when forced to articulate relative preferences with respect to each criteria,
and to articulate the relative importance of the criteria. In other words, this strategy is

preferred until it is deconstructed and evaluated in pieces.

89

Sensitivity Analysis

To gain a deeper understanding of the stakeholders’ reduction strategy priorities, a
sensitivity analysis was run on each data set using Expert Choice. Sensitivity analysis
allows the researcher to test “what if?” scenarios, i.e. the sensitivity of the reduction

strategy priorities with respect to changes in the weighting of the evaluation criteria.

Expert Choice provides four graphical sensitivity analysis modes: dynamic, gradient,
performance, and two-dimensional analysis and depicts how well each alternative
performs on each criterion when increasing or decreasing the importance of the criteria.
Its purpose is to assess that stability of an optimal solution under changes in the

parameters.

Utility Industry Sensitivity Analysis
The overall emission reduction strategy priorities for the utility industry survey group are:
0 Risk-based emission limit (.392)
o Multi-pollutant regulation (.177)
0 MACT numerical limit plus trading (.145)
0 MACT numerical emission limit (no trading) (.124)
o Receptor-based emission limit (.1 13)

o MACT technology standard (.049)

When the sensitivity analysis was run with respect to the criterion compliance flexibility

(.119 importance weight), the preference for the numerical emission limit plus trading

90

strategy increases as the weight of the criterion increases, ultimately reaching second in

the preference order. The preference level does not increase enough to replace the risk-

based emission limit as the most preferred strategy, though.

Figure 13: Sensitivity of utility industry strategy preferences to changes in
compliance flexibility criterion weight

 

 

.30

.20

 

 

 

 

 

 

 

 

 

 

Alfie
r
i
l
i
l
N l
I
I
i- I
i
i
'— I
l
l
l
l :—=' '
I a_ . .. .
>— //
|
L / '
p/ I
I
l
l
l
i
I
I l 1 I l L | l | n I
71 . .5 .I .7 .l .9
Priority (1 Coupler».

 

Multi-poll
MAcinnaFr

MACT tech u

 

Varying the importance weight of the planning certainty criterion (.98) has a significant
impact on the top rated risk-based standard. The preference level decreases from .392 to
.222 as the importance weight for planning certainty increases. These results indicate
that, if this criterion were more important to the utility industry (>.902), the multi-
pollutant regulation, which increased in preference from .177 to .249, would be the most
preferred mercury emissions reduction strategy, but only by a small margin. The results
also imply that, according to the utility industry, the risk-based standard does not provide

much planning certainty, but this is not an issue because planning certainty is not an

91

 

important evaluation criterion relative to the others.

Figure 14: Sensitivity of strategy preferences with changes in planning certainty
criterion weight

 

 

 

 

 

 

 

 

 

 

 

 

 

.50 Aim 1
i
L. l
I
I
i
.30 L— I
I
I- I Muilrpoll
: . 13“,}..1};
.20 ~— I
"‘ I "77 CTn‘p'.
" ' MACTnumer
I W'
.10 — i
I
I
l
I
l I i I . I . l I ‘1
'00 1 2 .4 .5 .6 .8 .9
Priorly d Flannhg C

 

 

 

The most sensitive utility industry criterion is political feasibility, although this criterion
was not given much weight relative to the other criterion (.061). As the importance
weight for this criterion increases, the risk-based standard decreases in preference order
from a strong first to fourth (.392 to .130), while the MACT numerical standard increases
from fourth to a strong first (.124 to .308). The MACT technology standard also increases
in preference from last to fifth (.049 to .125). These results indicate that the utility
industry does not believe that the risk-based emission limit is politically feasible, but this
criterion is not of much concern relative to the other criterion when evaluating preferred

options.

92

Figure 15: Sensitivity of utility industry strategy preferences to changes in
political feasibility criterion weight

 

 

 

 

 

 

 

 

 

 

 

11%
.50 A r
I
I
.40 \
I
I
I
I
_ :
I
I
, Mum-poll
.20 P— : -.“' ' «nuflirpfit
/ I ' " .‘r ".
/ I
.10 b— I
1
fl
b—I-i I
l
l I I I u l i l i l t I I l l l l I I
'00 .f .T .f .4 .5 .6 .7 .6 .9
Priority oiPolltlcal

 

 

 

Scientific defensibility is an important evaluation criterion for the utility industry (.250),
but variations in its weight do not have much impact on the strategy preference order.

The preference strength for this strategy with respect to scientific defensibility is so

Figure 16: Sensitivity of utility industry strategy preferences to changes in
scientific defensibility criterion weight

 

 

 

 

 

 

 

 

 

.00 A166
L —
,so ._
.‘o /
.30 '—
20 x
\\ ? K‘. _ E ’
w ~\ \fi‘ émutfip'oi
e W :‘MACTnun p
MACTnumer
MACT techn
.w I i I I I I I L I I I I I I I I
.1 .2 T .0 .5 .0 .7 .0 .0
Priority (1 Sclenlilc

 

 

 

93

strong that even if that criterion itself were unimportant to the group (a weight of 0), the
risk-based strategy is still strongly preferred (.343), and increases in preference with the

criterion importance weight (to a maximum of .545).

The legal feasibility criterion does not appear to be of relative importance to the utility
industry (.074), but its importance weight does have an impact on preference order. If this
criterion were considered relatively important, all of the strategies would be preferred
relatively equally, the preference for the risk-based strategy would decrease from .392 to
.216, the numerical emission limit would increase in the preference order from fourth to
second (from .124 to .199). The risk-based strategy still would remain the most preferred

alternative.

Figure 17: Sensitivity of utility industry strategy preferences to changes in legal
feasibility criterion weight

 

 

 

 

 

 

 

 

 

 

 

.50 A106
‘0 N

I
.30 —

I ' MACT rumor
2° — ..

Multl-poil

_ W
.10 F- // if.“ -- I "If!" I,
.00 I I l l I l . | l I ' ' | . I .

 

Priority oi Legal Fees

 

 

 

94

The cost benefit criterion is considered the most important evaluation criterion relative to
the others (.248), but, similar to the scientific defensibility criterion, variations in its
weight do not have much impact on the strategy preference order. The preference
strength for all the criteria remain fairly equal except for the risk-based strategy, which is
preferred twice as much as the next most preferred strategy and only increases in strength

from there (to a maximum of .480).

Figure 18: Sensitivity of utility industry strategy preferences to changes in cost-
benefit criterion weight

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A1196
.50
.‘o /
.30 ~
.20 P Mu lti - poll
.10 »—
.M v | - I a r r l . l u I r i r i o i
.1 7 .3 .4 .5 .6 .7 .8 .9
Priority oi Coat-Benet

 

 

 

With respect to the effectiveness, economic feasibility, and technological feasibility
criteria, small to no changes in preference order were observed after performing the
sensitivity analyses, indicating that these factors do not influence the utility industry’s
strategy preferences. This is validated by the low importance weights assigned to the
effectiveness technological feasibility, economic feasibility criteria, which are .041, ,

.041, and .052 respectively.

95

In summary, no variations were observed with respect to the most preferred strategy (i.e.
the risk-based emission limit) except in terms of planning certainty and political
feasibility. A small variation in the preference order is observed with respect to planning
certainty, as the multi-pollutant strategy is preferred slightly over the risk based strategy
(a difference of .027). A larger variation is observed for political feasibility, where the
MACT numerical emission standard advances to first from fourth in the preference order,

and the risk-based standard drops to fourth.

Large variations in the final rating indicate that more effort should be spent on verifying
the particularly sensitive criterion. The only criterion for which this applies is political
feasibility. Even though either no or small variations are observed for all but one of the
criterion, the AHP has not produced the optimal reduction strategy for the utility industry.
The sensitivity analysis for the utility industry survey group results indicate that a more
optimal strategy is one that is viewed by the utility industry as political feasible.
Alternatively, it is possible for the risk-based strategy to be the best alternative if the

political hurdles are overcome that currently render the strategy infeasible.

Environmental Organization Sensitivity Analyses
The overall emission reduction strategy priorities for the environmental organization
survey group are:

0 Multi-pollutant regulation (.324)

0 MACT numerical emission limit (no trading) (.251)

- MACT technology standard (.132)

96

o Risk-based emission limit (.119)
0 MACT numerical limit plus trading (.094)

- Receptor-based emission limit (.079)

When the sensitivity of the criterion technological feasibility was tested, the overall
preference order changed slightly as the weight was increased. The multi-pollutant
regulation drops to the second most preferred strategy in terms of technological
feasibility (.297), and the MACT numerical emission standard rises to the most preferred
(.348). Although this is a variation in the preference order, the multi-pollutant strategy is
still preferred strongly relative to the remaining strategies, so this does not decrease the

robustness of the AHP-determined top strategy choice.

Figure 19: Sensitivity of environmental organization group strategy preferences
to changes in technological feasibility criterion weight

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

.00 I” 1
I
l
/ MACT numm
I
I
I
i-fl‘i I
i
I
20 .—
I
I
I
l
.10 >—
I
I
I
I
_m . l r i . l . l u r r l I . l . r r r u
j .2 .3 .1 .5 .0 .7 .0 .0 1
Priority d Technologl

 

 

97

A large variation in preference order is observed when the legal feasibility criterion is
given greater weight. The multi-pollutant strategy is less preferred with respect to this
criterion, moving down to third in the preference order with a preference level of .144.
The top two reduction strategies with respect to legal feasibility are the MACT numerical
emission standard (.333) and the MACT technology standard (.250). This is not
surprising, since these are the two strategies that are explicitly mentioned in the Clean Air

Act as reduction strategy alternatives to reduce hazardous air pollutant emissions.

Figure 20: Sensitivity of environmental organization group strategy preferences
to changes in legal feasibility criterion weight

 

 

     

 

 

 

 

 

 

 

 

.40 AM I
I
\ I
I
I
.30 _ ;
I
~___/ .
I
I
20 I— I
I
I- , 'flulibpr)“
/ I
.10 ; ' ,1
I 7 accepted,-
I
b I
I
I
I I I I I I I I I I I l I I I I I | I
'00 .1 .. .3 I .5 .8 .7 .8 J 1
Puorlty 0! Log! Fen

 

 

 

With respect to the other evaluation criteria, no variations were observed in terms of the
most preferred reduction strategy, the multi-pollutant regulation. The variation in
preference order with respect to legal feasibility is large, though. Even though either no
or small variations are observed for all but one of this criterion, the AHP has not
produced the optimal reduction strategy for the environmental organization survey group.

The sensitivity analysis results indicate that a more optimal strategy is one that is viewed

98

by the environmentalists as legally feasible. Alternatively, it is possible for the multi—

pollutant strategy to be the best alternative if enabling legislation is passed.

An interesting observation the sensitivity analysis revealed involved the political
feasibility criterion and the multi-pollutant strategy. Although the multi-pollutant
strategy rates slightly lower when evaluated with respect to political feasibility compared
to overall (from .324 to .227), it still remains the most preferred strategy relative to the
others. This is surprising, since new laws would have to be enacted to enable
implementation of this reduction strategy, which may create political hurdles. It appears
that the environmental survey group believes that the stakeholders involved in the
mercury regulatory determination favor the multi-pollutant strategy, and that little

opposition will occur enacting it into law.

Figure 21: Sensitivity of environmental organization group strategy preferences
to changes in political feasibility criterion weight

 

Mult'I-poll

MACT nu mcr

MAcrIecm
I n‘ as:

 

Morn] of Pdllcfl

 

 

 

99

Governmental Agency Sensitivity Analysis
The overall emission reduction strategy priorities for the government agency survey
group are:

0 Multi-pollutant regulation (.267)

0 MACT numerical emission limit (no trading) (.242)

o MACT numerical limit plus trading (.206)

- MACT technology standard (.097)

o Receptor-based emission limit (.097)

o Risk-based emission limit (.091)

The sensitivity test for the compliance flexibility criterion yielded a variation in the
strategy preference order for the government agency survey group. When compliance
flexibility is given more importance, the multi-pollutant regulation is no longer the most

preferred strategy with respect to compliance flexibility. The MACT numerical emission

Figure 22: Sensitivity of government agency group strategy preferences to
changes in compliance flexibility criterion weight

 

 

 

‘JIIltIpoll

 

 

 

 

MACTtechn

 

 

L -_.4L..L_L~ _ L

l 1 l L l L 1 r J 1 L 1 1 I
(I .1 .2 .3 .4 .5 .6 .7 .0 .9 1

 

 

Pnorlty oI Cowllence

 

 

 

100

regulations with and without trading (.290 and .275, respectively) become the preferred
strategies. Although not ranked the highest, the preference for the multi-pollutant strategy

is still fairly strong (.210).

A large variation in preference order is observed when the strategies are considered with
respect to legal feasibility. The multi-pollutant strategy not only drops from first to third
in the preference order, it is preferred 2.25 times less. The MACT numerical and
technology standards increase in terms of preference to .333 and .250, respectively. These
results suggest that the government agency survey group does not believe that the multi-
pollutant strategy is legally feasible, which is not surprising since new laws would have

to be enacted to permit such a strategy.

Figure 23: Sensitivity of government agency group strategy preferences to
changes in legal feasibility criterion weight

 

 

 

 

 

 

 

 

 

A105
.30
I
\ '
I
I
.
1° _ .‘
i .
L ‘ ‘- .
I Mum-poll
I
.10 '
I
I
I
I
I
. I I I I i I I I l I I I I I I I I I I
00 .1 .2 .3 .4 .5 .6 .T .l .9
Priority of Legal Fees

 

 

 

101

With respect to the other evaluation criteria, no variations were observed in terms of the
most preferred reduction strategy, the multi-pollutant regulation. The variation in
preference order with respect to legal feasibility is large, though. Even though either no
or small variations are observed for all but one of this criterion, the AHP has not
produced the optimal reduction strategy for the government agency survey group. The
sensitivity analysis results indicate that a more optimal strategy is one that is viewed by
the government agency survey respondents as legally feasible. Alternatively, it is possible

for the multi-pollutant strategy to be the best alternative if enabling legislation is passed.

A couple of interesting observations were made while performing the sensitivity analysis
with respect to the political feasibility criterion. This criterion is not sensitive with respect
to the most preferred strategy, the multi-pollutant regulation, which infers that the

government agency survey group does not believe there are significant political barriers

Figure 24: Sensitivity of government agency group strategy preferences to
changes in political feasibility criterion weight

 

 

 

Mu III- p0 II

 

 

 

10 MAC T techn

 

. ' . I
{wt-11
"'1‘

I Boo-um

 

 

 

I I I I I I I I I I i I I I I I I
'°° .T .2 .5 .4 .s' 8 .7 .r .9 1

Prlorlty oI Pomlcal

 

 

 

 

 

102

that would hinder this strategy. Even more interesting is the observation made when
analyzing the variation in preference strength of the MACT numerical emission limit plus
trading with respect to the political feasibility criterion, which is .222 (compared to .094
overall). This result suggests that the government agency respondents believe that
emissions credit trading is politically feasible, which is surprising since a great deal of
uncertainty surrounds whether or not emissions credit trading is legal for hazardous air

pollutants under the Clean Air Act and safe for humans and wildlife.

103

CHAPTER FIVE

CONCLUSIONS AND RECOMMENDATIONS

This thesis evaluated different strategies for reducing mercury emissions from coal-fired
power plants and demonstrated an application of the AHP as a support tool for
determining the most preferred mercury reduction strategy among three stakeholder
groups. This chapter highlights the key findings of the study, evaluates the AHP as used
in this application, and identifies further research opportunities. In particular, the
potential role of the study outcomes in advancing the current debate over future mercury

emissions reduction strategies is examined.

SUMMARY OF KEY FINDINGS
Below is a summary of the key findings from this study, which are expanded upon in the
sections that follow.
I The receptor-based strategy scored consistently poor with respect to all the
criteria across all three stakeholder groups.
' The risk-based standard is a controversial strategy.
.I The utility industry group prefers the risk-based standard. To optimize this
strategy, it would have to be politically feasible.
' The environmental and government agency groups prefer the multi-pollutant

strategy. To optimize this strategy, it would have to be legally feasible.

104

I There is the potential for consensus with regard to the multi-pollutant approach.
' Scientific defensibility is a relatively important criterion to all three stakeholder

groups, but definitions for this criterion may differ.

Selection of an Optimal Strategy

After the criteria weights and paired comparison results were synthesized, one clear
finding surfaced. Certain aspects of the strategies under consideration were not popular
with any of the stakeholder groups. Of all the reduction strategies evaluated, the receptor-
based strategy scored consistently poorly with respect to all the criteria across all three
stakeholder groups. Overall, this strategy is the least preferred among the environmental
and government agency respondents (.079 and .097, respectively), and ranks second to
last among utility respondents (.113). These results indicate that this reduction strategy is
not a viable solution in selecting an optimal mercury reduction strategy for coal-fired

power plants and should no longer be considered as an option.

It is also clear that the risk-based standard is a controversial strategy. Extreme values
were assigned to this strategy with respect to each evaluation criterion, but on opposite
ends of the relative preference scale. The utility industry group rates this strategy high
with respect to all the criteria, while the environmental and government agency groups
rate it low. Overall, the risk-based standard was the most preferred strategy for the utility
group, preferred 2.2 times more than the next most preferred strategy. The environmental
and government agency groups, though, do not favor this strategy, ranking it last and

fourth overall. The extreme ratings given to the attributes of this strategy by all

105

stakeholder groups may be the result of a certain degree of strategic voting on the part of

the stakeholder groups. This is a reflection of the polarizing nature of this strategy.

The sensitivity analysis revealed that there is no scenario that could be proposed to
optimize this strategy. Although the utility industry group prefers this strategy to the
others, they would have an extremely hard time getting buy-in from the other
stakeholders. As stated above, the environmental and government agency groups rated
this strategy poorly with respect to all the criteria, but the most critical issues that would
need to be addressed to increase these groups’ comfort level with this strategy include

technological feasibility, planning certainty, and legal feasibility.

The study results also reveal that all three stakeholder groups approve of the multi-
pollutant reduction strategy. The groups unanimously agree that it is the best strategy in
terms of planning certainty, and also rate it favorably in terms of cost-benefit. Overall,
the environmental organization and government industry stakeholder groups favor this
strategy over any other, while the utility industry rate it as their second most preferred

strategy.

These results suggest that there is the potential for consensus with regard to the multi-
pollutant approach for reduction mercury emissions from coal-fired power plants. The
critical issue that must be addressed to optimize this strategy is legal feasibility. All three
groups rate the multi-pollutant regulation approach poorly with respect to this evaluation

criterion, which is not surprising given that there is currently no legal mechanism

106

available to implement this strategy. This is not an impossible barrier to overcome,
though, as there is broad support for this strategy. In fact, all three groups rate this
strategy high in terms of political feasibility, suggesting that they believe no significant
political barriers exist that would hinder legalization and implementation of this strategy.
It is clear that there is an opportunity for strategy optimization here, given the broad

agreement on this approach.

Optimization of the Matti-Pollutant StrategI

Adoption of a multi-pollutant regulation strategy would result in the EPA establishing
and promulgating emission standards for multiple pollutants (e.g. NOX, C02, 80;, and
Hg) at one time. It is evident that at this broad conceptual level there is support for such a
strategy across the stakeholder groups. Yet there is still the major issue of what
mechanisms would be employed to achieve the strategy. For instance, the four pollutants
to be addressed with this strategy could be reduced using the risk-based standard (the
utility industry group’s most preferred strategy) or the MACT numerical standard (the
environmental and government agency groups’ most preferred strategy next to the multi-

pollutant strategy).

The fact that at present the details of a multi-pollutant strategy have not be identified
means that while there is currently support for the concept, one or more of the
stakeholders might reject the specifics of the strategy once they are defined. Thus

stakeholder acceptance, which on the surface appears strong for the multi-pollutant

107

regulation approach, is likely contingent on acceptable mechanisms being selected in

realizing this strategy in its fully developed form.

Despite this, the fact that the details of a multi-pollutant strategy have yet to be defined
also represents an opportunity. It provides an opportunity to bring the key stakeholders
together to work collaboratively in fleshing out the elements of a multi-pollutant strategy.
It is clear from the interviews and survey responses that the stakeholder groups possess
certain perceptions of each other that may not be valid. For instance, the groups tend to
view themselves as being further apart than they really are and fail to see the large extent
of common ground that already exists. Valid or not, the perceptions which the
stakeholders groups have of one another are barriers to achieving a mutually acceptable
solution. Instead, it is more likely to result in strategic posturing and positional
bargaining. A decision-making process designed to bring these groups into closer contact
with one another, early in the multi-pollutant strategy development process, might well

assist in reshaping perceptions and reduce positional bargaining practices.

The study findings could assist in the formulation of one or more versions of a more fully
elaborated multi-pollutant strategy. For instance, the information regarding which criteria
the respective stakeholders value most would aid in the formulation of strategy options
that focus on interests rather than positions and the development of a strategy(ies) that

offers mutual gains for the stakeholders (Fisher et al. 1991; Susskind et al. 2000).

108

The study findings also point to issues that will require a lot of work to resolve and which
could be potential stumbling blocks in negotiating a multi-pollutant strategy that is
mutually acceptable to all. This would allow the negotiation process to dedicate the
degree of effort and resources necessary to resolve such key contentious issues. The issue
of scientific defensibility is one such issue. All three groups place a lot of importance on
a mercury emission strategy being scientifically defendable. Yet the significant
differences in how they evaluated the same strategies on this criterion suggests that they

have quite different conceptions of what scientific defensibility means.

AHP AND GROUP DECISION MAKING

During the course of this study, some strengths and weaknesses of the AHP were
observed. An obvious strength of the method is that it enabled the collection of all the
relevant elements of the problem into one model that can be interactively manipulated to
reveal interdependencies and potential consequences. The AHP’s reliance on pairwise
comparisons add to this strength by forcing the stakeholders to articulate the relative
importance of the evaluation criteria and then to decide the relative contributions of the
alternatives to the criteria. This strength was magnified even more in this study with the
in-depth interviews that were conducting prior to structuring the hierarchy, which
resulted in the inclusion of accurate decision elements. The stakeholders now have an
overall model of the mercury reduction strategy problem, which structures the problem
and enables them to see all the factors along with their relative importance and

consequences.

109

Another strength of the AHP is the sophistication and user-friendliness of the Expert
Choice software. The AHP is based on a complex mathematical calculation that uses the
eigenvalue method to produce a vector of composite weights that serve as ratings of
decision elements in achieving the most general objective of the overall problem (Saaty
1980). Having this computational algorithm available in a computer software program
reduces the time involved in addressing multi-criteria decision problems and reduces the

complexity of the process to enable AHP novices to employ this valuable method.

Expert Choice not only performs the necessary calculations quickly, but also includes a
feature that requires the AHP user to make fewer pairwise comparisons, thus increasing
the speed of the hierarchy evaluation process. By using this feature, only 53 pairwise
comparisons were required to calculate strategy priorities in this study, compared to the
405 comparisons that would have been required otherwise. The disadvantage of using
this feature, though, is that the Expert Choice user is not able to take advantage of its
inconsistency measure, which indicates when a stakeholder has made an inconsistent
judgment. Also, the use of this feature results in less data, which decreases the validity of

the results.

SUGGESTIONS FOR FURTHER STUDY
It is evident that, at a broad conceptual level, there is support for the multi-pollutant
strategy across the stakeholder groups. Yet there is still the major issue of what

mechanisms would be employed to achieve the strategy. Further work should be done to

110

convene the key stakeholders and investigate the elements of a multi-pollutant strategy

collaboratively.

Another area that requires more research involves the evaluation criteria. As mentioned
above, some of the pairwise comparison results suggest that the stakeholders may use
different definitions to describe some of the criteria. Although concise definitions were
provided to the survey respondents, the potential for personal interpretation was still a
risk. Therefore, research that identifies mutually agreed upon conditions that must be

met in order to satisfy each criterion is needed.

A larger sample size would also be desirable in performing a similar study. For the
purposes of this study, and considering the length of the survey and the number of
questions asked, the response rate met the researchers expectations. A larger response

rate would have increased the validity of the study, though, and is therefore desirable.

One possibility for achieving more study participants is to convene each stakeholder
group for a meeting, preferably in conjunction with an event at which they are already
attending. This way, you have access to a captive audience that does not have to make
special arrangements or major time commitments to participate. Also, this would enable
the researcher to run a “live” AHP session, where the decision hierarchy is developed as a
group and judgments are made and entered into the Expert Choice software using a

computer touchpad. Using this approach may also enable the researcher to acquire

11]

complete sets of pairwise comparisons, as opposed to the minimal number gathered for

this study.

112

APPENDICES

113

APPENDIX I

TOXICOLOGICAL ASPECTS OF MERCURY

ENVIRONMENTAL CHEMISTRY OF MERCURY

Mercury is a naturally occurring elemental metal that has three stable oxidation states:
Hgo, Hg”, and Hg”, each of which form complexes with many different elements —
resulting in numerous inorganic and organic mercury compounds (Nriagu, 1979).
Because the speciation of mercury and its chemical and physical form determine its fate,
transport, toxicity characteristics, and chemical behavior, it is important that these
parameters are taken into account when studying the mercury cycle and its impact on

human health and the environment. (Constantinou et al. 1995; Nriagu 1979).

Metallic mercury is the non-polar, elemental form of mercury. At ambient temperatures
and pressures Hg0 is a heavy, shiny, silvery-white liquid metal; the only metal that is a
liquid at room temperature. In its liquid form, mercury is reactive in the environment, and
readily converts to inorganic mercury. Metallic, or elemental, mercury is water insoluble
and extremely volatile under ambient conditions, easily vaporizing into a colorless,
odorless gas (EPA 1997b). Because of its high vapor pressure, exposure to elemental
mercury is primarily via inhalation. In the U.S., dental amalgams are the major source of
exposure, containing 43-54percent elemental mercury (ATSDR, 1997). Recent studies

conducted by Health Canada (1995) have indicated that dental amalgams may be

114

responsible for 37 percent of the total mercury intake in individuals with mercury-

containing fillings.

Elemental mercury can react with other elements to form inorganic mercurous (Hg+’) and
mercuric (Hg+2) salts, such as mercuric chloride (HgClz) and mercurous sulfate, and
Cinnabar (HgS), the most abundant mercury-bearing mineral on the Earth’s surface. Of
the two inorganic species, the divalent form is most often found in the environment and is
of more biological and environmental importance than the mercurous species (Nriagu,

1.0. 1979).

While the majority of mercury released into the environment is in the inorganic form,
biological processes convert inorganic mercury into organic mercury. Once mercury is
available in an aquatic environment, it can be methylated (addition of a CH3 group).
Methylation of mercury occurs abiotically in suspended bottom sediments and biotically

by sulfate-reducing bacteria as part of an intracellular process (Nriagu, 1979).

The mercury compounds that are most often found in the environment are the mercuric
salts mercuric chloride (HgClz), Cinnabar (HgS), and mercuric hydroxide Hg(OH)2; the
methylmercury compounds methylmercuic chloride (CH3HgOH) and methylmercuric
hydroxide (CH3HgCl); and, in small fractions, dimethylmercury and phenylmercury
(EPA 1997b). According to the National Research Council (2000), the chemical species
of mercury that are of toxicological importance (and, therefore, significant for this thesis

and discussed in detail below) include the inorganic forms metallic (Hgo). mercurous

115

(Hg+'), and mercuric (Hg’z) mercury, and the organic compounds methylmercury

(MeHg), dimethylmercury, and ethylmercury.

MERCURY FATE AND TRANSPORT

Mercury is a naturally occurring element that, like all elements, exists in the same
quantities now as when the Earth was first formed. Geologically bound mercury is
mobilized via natural processes or human activities, which begin its cycling in the

environment (Nriagu 1979). (See Mercury Sources section below for more information).

Whether by natural or human-influence, once mercury is mobilized it cycles to the
atmosphere where it is transformed and transported, deposited from the air to aquatic or
terrestrial environments, and sorbed onto soil or sediment particles where the cycle
repeats itself (revolatilization from land and surface water to the atmosphere) (see Figure
25.) Although the movement and distribution of mercury can be soundly described, the

detailed behaviors of mercury in the environment remain a point of debate.

About half of total anthropogenic mercury emissions enter the global atmospheric cycle
(Mason et al., 1994), while the remainder is transported a lesser distance and removed
through local or regional cycles (EPA 1997b). Elemental mercury partitions strongly to
air and is more abundant in the atmosphere than the oxidized forms (e. g., mercuric and
methylmercury), which constitute less than two percent of the total atmospheric
concentrations. (Watras and Huckabee, 1994; Fitzgerald, 1986, 1989). Because of its

insolubility in water, elemental mercury resonates in the atmosphere for about one year

116

 

 

3...... Leghassa 1

 

 

 

    

.3 $4....

 

 

 

   

and... 3:29.: 52526:. 33;

A . . fl
:35ng 3:5.“ .3. .38...

 

 

 

293 .33qu 2E. "ma aha—ME

117

and, hence, can be widely dispersed and transported long distances. In contrast oxidized
mercury is deposited quickly (hours to months, dropping within 100 km from the source),
returning to land and water via wet and dry deposition (EPA 1997b). A recent review
paper suggested that 50-85 percent of mercury released to the atmosphere via coal
combustion and incineration is in the oxidized form, which is more readily deposited

locally or regionally (Carpi 1997).

The fate of mercury deposited in soils will depend on the chemical make-up of the soil
and other factors. Typically, mercury forms inorganic compounds in the soil, including
mercuric sulfide, oxide, and chloride. Mercuric sulfide and oxide have low solubilities,
so the mercury in these forms will generally not be as mobile as that in mercuric chloride.
Formation of complexes with organic matter limit the mobility of mercury in soil. Soil
thus serves as a large “sink” for mercury, and can act as a slowly releasing source (EPA,

1997a).

Soil mercury can also be converted to organic mercury. Approximately 1-3 percent of
soil mercury is organic mercury (primarily methylmercury) while the remaining 97-99
percent is inorganic mercury. A small fraction is metallic mercury, which tends to

volatilize quickly due to its relatively high vapor pressure (EPA 1997a).

Mercury enters the aquatic ecosystem via atmospheric deposition, runoff, and

groundwater leachate. Similar transformation and complexation processes that occur in

the soil environment also occur in aquatic sediments. Within the water column, 25percent

118

or less of the available mercury is organic (methyl) mercury (EPA 1997a). The majority
of mercury in the water column is dissolved inorganic mercury, or inorganic mercury
complexed with organic material. Although organic mercury may makeup a very small
percentage of total mercury in the aquatic environment, it can bioaccumulate to high
concentrations in certain biota. The majority of mercury absorbed by biota is organic
(methylated) (EPA 1997a). Once in water, mercury can be removed from the water by
deposition to sediments, volatilization to the atmosphere, or absorption by aquatic biota.
As with many other chemicals, mercury cycling in aquatic systems is dynamic, so that

once released by human activity, it is quite difficult to effectively remediate.

Scientists now believe that atmospheric deposition is responsible for the bulk of mercury
loading to terrestrial and aquatic ecosystems. A study examining mercury in sediments
found that yearly atmospheric deposition of mercury has increased from 3.7 to 12.5 ug/
square meter since 1825 in northern Wisconsin and Minnesota (Enstrom DR. and EB.
Swain 1997). Whole blood levels of mercury in loons follow an increasing gradient from
West to East across North America (Evers et. al. 1998). This trend is consistent with
predicted atmospheric deposition patterns found by US. EPA using a computer model

that simulates regional mercury transport and deposition (EPA 1997a).

Another study indicated that northern Michigan receives half of the precipitation mercury
loading that southern Michigan receives (Hoyer et al. 1995). The data suggests that the
mercury deposited originates at least in part regionally; proximity to known

anthropogenic sources of mercury to the atmosphere was correlated with mercury loading

119

to the study sites. A recent paper predicted that approximately 83 percent of atmospheric
loadings of mercury to the Great Lakes were due to anthropogenic emissions (Shannon,
JD. and EC. Voldner 1995). Other researchers have looked at the response time of the
environment to reduced mercury emissions from human activity. A paper estimated that
elimination of the entire anthropogenic load in the oceans and atmosphere would take
fifteen to twenty years after a complete cessation of direct and indirect anthropogenic

mercury emissions (Mason et al. 1994).

During the 1970’s, the mercury burden in Great Lakes herring gull eggs was spatially
variable; highest levels were found in Lake Ontario and Lake Superior. Spatial variation
may have indicated variation in loading to the lakes. The early 1990’s data, however, is
characterized by more evenly distributed mercury burdens distributed across the Great
Lakes. This is thought to be the result of a shift from point source loading of mercury to

diffuse non-point source loading (especially atmospheric deposition) (Koster et al. 1996).
A recent review used a weight-of-evidence approach to assess multiple studies relating to
long-range atmospheric transport of naturally and anthropogenically derived mercury.

The following conclusions were reached (Koster et al. 1996):

0 Approximately 5000 tons of mercury are released to the environment annually, 4000

of this can be attributed to human activities.

120

0 Approximately 3000 tons of the total yearly anthropogenic mercury loading to the
atmosphere is transported over several thousand kilometers due to atmospheric
circulation patterns.

0 Mercury in the sediments of remote lakes is primarily derived from recent airborne
deposition rather than re-mobilization.

0 Atmospheric deposition to remote aquatic and terrestrial systems is resulting in
bioaccumulation of mercury in fish and wildlife.

0 Acid precipitation can increase the bioaccumulative properties of mercury.

The evidence demonstrates that anthropogenically derived mercury levels have increased
since the industrial period, and this mercury is subject to long-range transport and
deposition far from the original source as a result of atmospheric circulation patterns
(Jackson, TA. 1997). Other authors reached the same conclusion in another recent

review (Fitzgerald, W.F. 1997).

SOURCES OF MERCURY

The US. EPA defines three major categories of mercury emissions: natural,
anthropogenic, and re-emitted mercury emissions (EPA 1997a). Re- emitted mercury
includes transfer of previously deposited mercury (released naturally or
anthropogenically) to the atmosphere via biological and geological processes. The fluxes
of re-ernitted mercury to the atmosphere are not clearly established; more study in this
area will be required to document and assess this potential secondary source, which can

contribute to long-term cycling of mercury in the environment.

121

Natural mercury emissions result from the release of mercury from geologic sources via
natural weathering processes, volcanoes and volatilization from soils, aquatic
environments, and vegetation to the atmosphere, and other geothermal activities (Nriagu,
J .O. 1979). A common mercury-containing mineral is Cinnabar (mercuric sulfide); most
commercial production of mercury has involved this mineral. Major mercury ore-bearing
zones are found in the circum-Pacific region and in the Himalayan and Mediterranean
regions. Major mercury mines historically have operated in California, Spain,
Yugoslavia, and Peru, although no primary mercury mining is currently done in the US.
(Nriagu, 1.0. 1979). Natural emissions are thought to be primarily n the elemental

mercury form (EPA 1997b).

Anthropogenic mercury emissions result from the release of geologically bound mercury
to the environment as a consequence of human activities. Although a great deal of
uncertainty remains, it has become increasingly evident that antrhropogenic emissions of
mercury rival or exceed natural inputs. According to EPA’s Mercury Report to Congress
(1997b), the amount of mercury mobilized and released into the environment has
increased by a factor of between two and five since the beginning of the industrial age.
Current estimates suggest that 50-75 percent of the total yearly input of mercury into the
atmosphere from all sources is the result of anthropogenic releases. A recent paper
reported estimates of global anthropogenic mercury emissions reaching as high as 71
percent of total mercury emissions if re-emitted anthropogenic mercury is considered in

the estimates (Jackson 1997).

122

US. EPA divides anthropogenic sources into two main components: point source, and
non—point source or area source (EPA 1997a). Point source emissions are sources that are
readily identifiable, such as the smokestack on an industrial plant. Non-point sources are
more difficult to define and locate, consisting of a large number of small, really dispersed
sources which alone may emit smaller quantities of mercury, but when considered
together become significant. Non-point mercury pollution can include mercury released
from paints, dental preparations, and fluorescent lamp disposal, among a multitude of
other potential sources. Municipal landfills can become aggregate sites of smaller

SOUI'CCS.

Major categories of anthropogenic point source emissions include combustion,
manufacturing, and miscellaneous sources (EPA 1997a). In these processes, mercury is
released from a stack in either gaseous or particulate forms. The speciation of mercury
emissions is thought to depend on the type of fuel used, flue gas cleaning methods, and
the operating temperature. Although methods for mercury speciation of stack emissions
are being refined, and there is still controversy in this field, gaseous mercury emissions
are thought to include both elemental and oxidized chemical forms, while particulate
mercury emissions are thought to be composed primarily of oxidized compounds

(ATSDR 1999).

In general, mercury emissions from combustion processes can either be measured directly

or estimated based on knowledge of the mercury level in the material burned, and the

123

amount of material burned. This latter approach is more common, but also generally
entails more uncertainties. Major sources of US. mercury emissions in total amounts and

percentages are given in Table 12.

Table 12: Major sources of anthropogenic mercury releases in the US. (EPA 1997a)

    

\li'rI‘IIr} Source 19944995 (Ions/scum Percent of Total 1m t‘IIIIII‘)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

COMBUSTION SOURCES
Coal-fired Utility Plants 51.6 32.6
Oil-fired Utility Plants 0.2 0.1
Coal-fired Commercial/Industrial Boilers 20.7 13.1
Oil-fired CommerciaVIndustrial Boilers 7.7 4.9
Municipal Waste Combustion 29.6 18.7
Medical Waste Incineration 16.0 10.1
Hazardous Waste Combustors 7.1 4.4
Sewage Sludje Incinerators l 0.6
Miscellaneous Combustion Sources 3.8 2.4
”Total Combustion Sources . ' ‘ 137.7 1 86.9 '
MANUFACTURING SOURCES
Chlor-alkali 7.1 4.5
Portland Cement 4.8 3.1
Pulp and Paper ManufacturinL 1.9 1.2
Instruments Manufacturing 0.5 0.3
Miscellaneous Manufacturflg Sources 1.3 0.9
' Total Manufacturing Sources, , _ 9 15.6 [ 7 , 7 - 10.0 A
AREA SOURCES
Lamp Breakage 1.5 1.0
Laboratory Use 1.1 0.7
Dental Preparations 0.7 0.4
Landfills 0.08 0.05
Total Area Sources , . i; . l . 7 1’ i 3.4 V . 7 V V 2.2
OTHER SOURCES
Geothermal Power 1.4 0.9
Total All Sources 158 100

 

 

 

 

Because of the relatively volatile nature of mercury and the particular sources that release
it, a much larger fraction of total releases to the environment consists of releases to the
air, rather than direct discharges to water or land. The total annual estimate for all
anthropogenic mercury emissions to the air in the US. for 1994-95 was 158 tons

(316,000 pounds) (EPA 1997a). While this estimate has a number of uncertainties, it is

124

likely low, due to lack of full accounting for mercury use at chlor-alkali plants (see
below), and possibly other poorly-characterized sources (i.e. mobile source emissions).

The largest source of mercury emissions on a national level are coal-fired power plants
(32.6 percent), municipal waste incinerators (18.7 percent), Commercial and industrial
boilers (18 percent) and medical waste incinerators (10.1 percent) (EPA 1997a).
Incinerators emit mercury when they burn wastes containing mercury. For medical waste
incinerators, waste mercury comes from medical devices like thermometers and blood
pressure cuffs. For municipal waste incinerators, mercury is in discarded appliances like

fluorescent lights, lamps, and thermostats.

Coal-fired power plants produce mercury by burning coal; the coal contains trace
amounts of mercury that are released during combustion. These plants are the single
largest source of mercury pollution in the U.S., and are responsible for 33 percent of the
total mercury emissions from all sources (EPA 1999d). In 1990, coal-fired power plants
emitted 46 tons of mercury, by 1994 emissions jumped another 10 percent to 51 tons, and

are expected to climb another 33 percent over 1990 levels, by 2010 (EPA 1998).

In addition to these industries, it is likely that mercury-cell chlor-alkali facilities (plants
that manufacture caustic soda and chlorine) are one of the top mercury emitters
nationally. Although these plants are estimated to produce 4.5 percent of the nation’s
annual mercury emissions, that estimate is certain to be very low. These plants use
enormous, heated baths of mercury in their manufacturing processes. In 1995 they used
in aggregate 165 tons of mercury — and reported emitting only 7.1 tons (EPA 1997a).

Because these plants do not incorporate mercury into their products or release mercury in

125

byproducts, they cannot account for the 100-plus tons they used but did not emit.
Although these plants cut their usage to 104 tons by 1998, the missing mercury, if
emitted into the air, would make the industry — only 10 plants -— the largest source in the

nation.

MERCURY EXPOSURE AND THREATS TO HUMAN HEALTH
Methylmercury and other forms of organic or inorganic Hg are poisonous to many living
organisms in both aquatic and terrestrial ecosystems, and there are many ways that a
person can be exposed to mercury through the environment, including (N IOSH 1973):
0 inhalation of elemental mercury vapors in ambient air at the work place (dental,
health services, chemical, and other industries that use mercury),
0 ingestion of drinking water and food contaminated with elemental mercury or
methylmercury,
0 release of elemental mercury during dental and medical treatments,
0 skin contact during use of mercury in the work place, and
0 exposure to above background levels in air, soil and water near hazardous waste

sites.

Although exposure to mercury can cause many health problems, exposure does not
necessarily mean that adverse health effects will result. Health effects depend upon the
amount of exposure, the form of mercury, and the route of exposure. For the general US.
population, dietary intake is the dominant pathway for human exposure to mercury, with
fish, marine mammals, and crustaceans that contain methylmercuy in their tissues being

the primary sources. (ATSDR 1999; NRC 2000). Another leading contributor to mercury

126

body burden in humans is inhalation of elemental mercury released from dental
amalgams (ATSDR 1997). Recent studies conducted by Health Canada (1995) indicate
that dental amalgams may be responsible for 37 percent of the total mercury intake in
individuals with mercury-containing fillings. Because of the variability in fish
consumption habits and number of amalgam fillings among the general population,
exposure rates are difficult to measure and, therefore, a great deal of uncertainty rests on

these figures.

When exposed to elemental mercury, toxic effects include effects on the central nervous
system (i.e., cognitive, personality, sensory, and motor disturbance), increased blood
pressure, tremors, rashes, and renal damage. Inhibition of the immune system may also
result. Fortunately, mercury is rarely found in the environment as the pure, confined
liquid metal, but rather in forms that generally have much lower vapor pressures than

elemental mercury (Nriagu 1979).

Due to the high water solubility of some forms of inorganic mercury (e.g., mercuric
chloride), the kidneys, which are primary targets for organ damage, process this form.
Toxic effects include renal failure, gastrointestinal disturbance, rashes, blisters and ulcers
to lips and tongue, weakness and muscle twitching, and elevated blood pressure. Because
of its ionic charge, mercuric Hg does not readily penetrate the blood-brain barrier or the

placenta (NRC 2000).

127

Fish consumption advisories have been deve10ped and issued to warn people about the
health risks of consuming merthylmercury-contaminated fish, shellfish, and wildlife, and
provide guidance as to the amount of fish and wildlife that can be safely consumed by
adults, pregnant women, nursing mothers, and children. Although advisories are issued
for fish that are contaminated by a variety of chemicals, including polychlorobiphenyls
(PCBs), dioxins, chlordane, and DDT, mercury contamination is the most frequent basis
for fish advisories (EPA 2000). As of July 2000, 40 states and one territory (American
Samoa) had issued fish consumption advisories for mercury. Of those states, 13 have
issued state-wide advisories, covering every inland lake and stream; the remaining 27
states issued advisories for more than 1,900 specific water bodies (EPA 2000). Table 13

gives ranges of methylmercury concentrations in certain types of sport fish.

Table 13: Range of Mean Mercury Concentrations for Major Fish Species

Largemouth bass .001-8.94

 

Smallmouth bass .008-3.34

 

Walleye .008-3

 

Northern Pike .10-4.4

 

Channel catfish .001-2.57

 

Bluegill sunfish .001-l.68

 

Common carp .001-1.8

 

White sucker .002-1.71

 

 

 

 

Yellow perch .01-2.14

 

Fish consumption advisories are based on various types of data. A “safe” intake rate for
a given contaminant is defined based on toxicological studies on animals and
epidemiological data on the effects of given contaminants on humans. Federal
Government agencies (e. g., EPA, FDA, ATSDR) issue recommendations on these intake

rates as part of their risk assessment programs. States collect data on the levels of

128

individual contaminants in fish in various waters. Selected water bodies are sampled in
efforts to obtain data that best represents all the state’s waters. It is important to know
how many water bodies were sampled in assessing the extent of mercury contamination

across a given state.

State officials then use assumed consumption rates (see Table 13) and, based on fish
tissue concentrations, issue advisories on the amount of fish that can be safely consumed
for particular water bodies. About 85 percent of adults in the US consume fish at least
once a month, about 40 percent of adults consume fish once a week, and 1 to 2 percent
consume fish almost daily (EPA 2000). Each state government has the authority to decide
which contaminants and fish species to issue advisories for, how strict those advisories
are, and whether to issue more strict advisories to sensitive populations such as women of
childbearing age, children, and high fish-consuming communities. Additional risk
assessment factors can also be factored in. A simple formula for the calculation is as

follows:

“Safe” consumption rate for a given fish = “Safe” intake rate for contaminant
Concentration of the contaminant in fish

Calculation of the “safe” intake rate for the contaminant is a key piece of this equation,
and has recently been under debate. The EPA and the Agency for Toxic Substances and
Disease Registry (ATSDR) have followed different approaches and utilized different core

studies in developing their safe intake level for mercury.

129

EPA terms its “safe” level of ingestion rate for a given contaminant the “reference dose”
(RfD). The current RfD for methylmercury is 1x10” mg/kg body weight/day, or 0.1
microgram (ug) Ikg -day. The RfD is based on epidemiological studies of a poisoning
episode in Iraq in the 19703, in which consumption of bread prepared from
methylmercury-contaminated grain lead to the deaths of hundreds of people. Based on
estimates of the varying degree of mercury exposure, researchers have estimated the

lowest levels at which mercury-related effects occurred.

The RfD is calculated using the following formula:

RfD = Benchmark Dose
UF x MF

where the benchmark dose is based on observation of effects at lower exposure levels,
MP is modifying factor, and UF is uncertainty factor. The purpose of the uncertainty
factor is to account for population variability, including variations in the biological half-
life of methylmercury, variations in mercury hairzblood ratios, the lack of two-generation

reproductive studies, and lack of long-term effects data.

ATSDR calls its “safe” level of ingestion for a given contaminant the “minimal risk
level” (MRL). The agency recently released a final Toxicological Profile for Mercury
that contained a revised MRL for methylmercury of 3.0x10'4 mg/ kg body weight/day, or
0.3 microgram/kg-day (ATSDR 1999). The MRL is based on statistical analysis of data
collected in the Seychelles Child Development Study, an ongoing study in the Republic

of Seychelles in the South Pacific. The researchers have investigated neurodevelopmental

130

impacts on children exposed to mercury prenatally. In contrast to ongoing work in the
Faroe Islands, the only mercury-related impairment found thus far in the Seychelles

studies was a decreased activity level in boys.

The MRL is calculated using the following formula:

MRL: NOAEL
UF

where the NOAEL is the “no observed adverse effect level”, based on the median hair
concentration of mercury in the highest 20 percent exposure levels (15.3 parts per million
in maternal hair), and an aggregate uncertainty factor of 4.5 was used to account for

variability discussed above.

State health agencies have the discretion in determining which risk level value they will
use in establishing its fish consumption advisories. ATSDR noted in releasing its
Toxicological Profile (1999) that its new MRL should not be used to set advisories.
Based on the current risk values, the EPA RfD will produce fish consumption advisories
that will be more restrictive, and will possibly be more protective of human health, than

the ATSDR MRL if it were used
If any states decided to use the new ATSDR MRL in determination of advisories, a

simple comparison shows the effects this would have compared to application of the

current EPA level. The following table shows the mercury fish tissue concentrations that

131

would be tolerable given different fish consumption rates, for a 50 kg (110 pound) person

(see Table 14).

Table 14: “Safe” Methylmercury concentrations in fish, based on EPA and ATSDR
risk approaches, and different consumption rates*

 

 

 

 

 

 

 

 

Fish Consumption Rate ”Safe” 11;: Concentration in Fish
Based on Two Risk Approaches
(g/d) EPA (ug/g) ATSDR (ug/g)
10 0.50 1.50
20 0.25 0.75
30 0.17 0.50
50 0.10 0.30
100 0.05 0.15
150 0.03 0.10
300 0.02 0.05

 

 

 

 

*: Assumes 50 kg (110 lb) person.

Table 14 shows that the three-fold higher intake threshold set by ATSDR would translate
into three-fold higher permissible fish tissue levels, for given consumption rates. This
also illustrates the importance of the consumption rates assumed by the states in

establishing their advisories.

The release of the ATSDR Toxicological Profile for Mercury lead to some uncertainty
among states regarding the appropriate risk approach to use, even though the agency had
stated that it does not recommend that states use the revised minimal risk level in setting
advisories. One year after the ATSDR report was released, the National Research Council
convened the Committee on Toxicological Effects of Methylmercury to evaluate old and
new data on health effects and risk guidelines. On the basis of body of evidence from

human and animal studies, the Committee concluded that EPA’s RfD for MeHg, 0.1

132

 

ug/kg/day, is a scientifically justifiable level for the protection of public health and

should be used by states for the development of fish consumption advisories (NRC 2000).

The US. Food and Drug Administration (FDA), which issues consumption advice for
commercial marine fish, also has established an action level for methymercury of 1 ppm,
Because shark, swordfish, king mackerel, and tilefish have been found to contain high
levels of MeHg in their tissue, the FDA has warned pregnant women and women of
childbearing age against consumption of these species (FDA 2001). As shown in Table
15, methylmercury levels in the top 10 species of fish, which make up approximately 80
percent of the seafood market including canned tuna, shrimp, pollock, salmon, cod,
catfish, clams, flatfish, crabs and scallops (FDA 1994), contain less than .21 ppm.
Because few people eat more than 2.2 pounds of these species per week, consumption

level warnings are considered unnecessary (FDA 1996).

Table 15: Methylmercury Concentrations in the top 10 types of fish consumed by
the US population (EPA 1997b)

Tuna .206

' .047
Pollack . 150
Salmon .035

Cod . 121
Catfish .020-. 160
Clam .023
Flounder .092
Crab . 177
.042

 

133

Because of its organic, lipophilic nature, organic mercury is the most toxic mercury form,
and methyl mercury is the form of organic mercury that is of greatest general concern to
ecological and human health (ATSDR, 1999; NRC. 2000). A spectrum of adverse health
effects were observed following exposure to MeHg, with the severity depending on the
magnitude of exposure and the susceptibility of the individual being exposed.
Populations at greater risk due to unusually high exposure include recreational and
subsistence anglers and Native American populations who routinely consume large
amounts of fish (ATSDR 1999). Susceptible populations, i.e., populations that will
exhibit a different or enhanced response to mercury than will the majority of people
exposed to the same level, include the elderly, people with pro-existing disease, and the
younges of the population (the unborn and children) because of their immature and
developing organs. Factors that influence a persons level of susceptibitliy include genetic
makeup, developmental stage, age, health and nutritional status, and substance exposure

history (e.g., smoking) (ATSDR 1999).

The developing fetus is considered much more sensitive to injury by MeHg exposure
than adults because of the potential for interference with the growth and migrations of
neurons, leading to irreversible damage to the fetal central nervous system (EPA 1997c).
Ingested methylmercury is almost completely absorbed into the blood and distributed to
all tissues (including the brain); it also readily passes through the placenta to the fetus and
fetal brain (EPA 1997c). Infants exposed to acute high doses of MeHg in utero were born
with sever disabilities, such as mental retardation, seizure disorders, cerebral palsy,

blindness, and deafness (see acute exposure studies section below). Prenatal low dose

134

exposure, resulting from chronic maternal consumption of contaminated fish, produce
infants that appear normal during the first few months of life but later display deficits in
subtle neurological end points (i.e., IQ deficits, abnormal muscle tone, decrements in
motor function, attention, and visuospatial performance). (see chronic exposure studies
section below.) The EPA estimates that about seven percent of women of childbearing
age are exposed to MeHg at levels exceeding the RfD of 0.1 microgram (ug)/kg/day, and
about one percent of women have MeHg exposures three to four times that level (EPA

2000).

The National Research Council July 2000 report completed a review of the latest
scientific evidence regarding the health effects of methylmercury. This literature review
indicates that MeHg causes a wide range of adverse effects in multiple organ systems
throughout the life span of exposed humans and wildlife. Although studies have been
conducted on the carcinogenicity, genotoxicity, immunotoxicity, renal toxicity, and
hematological and reproductive effects of MeHg, the endpoints that are the most widely

studied relate to neurotoxic effects.

The database on neurodevelopmental effects is extensive and includes studies

documenting neurological dysfunction and developmental abnormalities that occur

following both acute and chronic mercury exposure (NRC, 2000).

Residents living near Minamata Bay, Japan were exposed to high doses of MeHg in the

1950’s from ingesting fish contaminated with methylmercury from chemical plant

135

effluent (Watanabe, C. and H. Satoh, 1996). This incident brought to light the severe
neurological dysfunction that can result from exposure to high doses of MeHg,
particularly when it occurs prenatally. Exposed children expressed mental retardation,
primitive reflexes, cerebellar ataxia (loss of coordination), disturbances in physical
growth, dysarthria (speech disorder), limb deformities, hyperkinesis (hyperactivity),
hypersalivation, seizures, strabismus (misaligned eyes), and pyramidal signs (difficulty
instigating, terminating, and altering movement). In addition, the incidence of cerebral

palsy among children identifies as suffering from congenital Minarnata disease was nine
percent, which is above the national incidence (NRC, 2000). According to one estimate,
the mean hair Hg concentration of mothers who gave birth to infants with congenital
Minamata disease patients was approximately 41 ppm (Akagi et al. 1998); significantly
higher than hair Hg concentrations of unexposed individuals, which ranges from .2 ug/g

to .8 ug/g (NRC 2000).

There is considerable scientific uncertainty surrounding the data gathered from the
Minamata poisoning incident because samples were not taken until the effects of the
exposure began to surface, which occurred five to eight years after the births. In Japan, it
is an old custom that the umbilical cords of newly-bom children are preserved by their
parents, so 151 archived umbilical-cord tissue were sampled dating from 1950 to 1969.
Results from those tests confirmed exposure increases during this period (Harada et al.

1999).

136

Another mercury poisoning epidemic occurred in Iraq in the early 1970s following the
consumption of wheat treated with a methylmercury containing fungicide. This incident
involved higher, more acute exposures that those experienced in Minamata Bay (NRC,
2000). Effects included severe sensory impairments, general paralysis, hyperactive
reflexes, crebral palsy, and impaired mental development, severe neurotoxicity, and death
(Watanabe, C. and H. Satoh, 1996; NRC, 2000). Maximum matemal-hair mercury
concentrations during the time when the study child was in utero served as the index for

fetal exposure and ranged from 1 to 674 ppm (Marsh et a1. 1987).

CHRONIC EXPOSURE STUDIES

Historically, most toxicological investigations centered on acute exposures. More recent
emphasis in environmental toxicology is on chronic, low dose exposures, since most
exposures affecting the general population are chronic and low-dose in nature, with diet
(fish consumption) as the primary route. A number of epidemiological studies have been
carried out on populations exposed chronically to low doses of MeHg. The table below
summarizes some key aspects of those studies. Endpoints that have been assessed include
status on neurological examination, age at achievement of developmental milestones,
infant and preschool development, childhood development, sensory, and

neurophysiological functions.

I37

 

 

 

 

 

 

 

 

 

 

 

5mm wfim I e. fins... 5% We
:UmU .505 5558.. 5%. 0.3 I n.
.._<H<:3 .315...» .0... 0-: .502 .E 2.5:. .00 00:2 ”5.... we .52: .522:
m3.
..0 .0 :00:.>:o :05 om z. .59.
:5. :5 .02. 0.0: E .0 SE 0. a w? 2.8:. 5 .05. a. $2. 005: ”a... .2 .502
moo.
.0 .0 :0m:.>:o
5%.
x00. .0 .0 ..0.x< 00:23.5 .S:05:0.0>0Q mm: 05:05 0. 5.8-0 0mg. .59. wh 5:02
.30. .5 .0 0.0.22 2.5:.
505.7.
8.50.... .50.. “0:05.
..30. ..... .0 50x2 .52.: .....I.. inane 55.0 5050.05.02 SEN... 05:05 me 0.3-0 0mg. 5%. a: 5::02 :5. 55052 0:. -xum
3.8 nm. WE 0... ..0 0.000 .0055: 05 :5 8. u... <mU2 0.: .0 0 :00 00:3:0200..::.n00.0a

05 :0 :55. 0.03 50.20.0000: 5:55 .38. n3 5n... SA. .02.»... 05 :5. A59. mvv 55:50:00 m: :5. 55.2.5 .0030. 0.: 5030: 0.5.0.. 01.. :0:..00: <Um2 05 .3 “.020... 00.000 0.0.0:.
03.5000 .50:0w .020 5:05 o: 05 .0”. 0050050 .00.“. 5.3 3.500%: x..::0....:w.m 0.03 50:5500500 w... :0..- 5:055 :m... 30:0.» 203 0.500.. 0.050.501. :5. .0555... :05: :5 :0:.:500
0.03 50.5...530 0335.83: :5. 55.0: :0...» 2.30.. MFmQD :5. 05.50:. MES: 50:05:85.0 m: :5.-...E0.:5 5003.0: :55. 0.03 5.5.0000: o: .020 0.003 87m .0". .2500. 00.8.00.
55:0. :00: .0 0:0. :5... .520 5050.050: .5505... :5. 03.50.3000 :5. 8:350:00 w: ...::..:E0.:5 503.0: .:0:.>0 0....» 5.5.0002. 0: .558 5050.050: :.0 0.003 87w 0.: .0". ”3.30m

 

 

 

 

 

 

 

 

550.5
5:53 .3455: .3: .502 :N 3.8:. 8 I. 005: n5... . s 5.3.2 :2...
:30. .0 .0 50:2 £05.:
5...: v.86. .0m5: 5%. 3:0..0
:30. .0 .0 50:2 Karma—D .530 5050—0502 mm: 8.003 87w .0 .50.: .50.. 0.: 55:02 :5. 5:052 vow .m0m
ll

 

A . m. ..0
m: 500% 0. :53. 5..» 3.500000 5.3.0.33 0.03 5.5.05.0. 125500.00: .0 00.5 0:... .3508: .0: 0.5 330 0.: .0 «5050.0 .50>0w .:0.=S .0 600:9: 600.0 .50 :0.:....0 :05? 5 00m: 05 :5
50.52.5500 m: :5...:E0.:E 503.0: :55. 0:3 8.5.0000: 50055.0 02 .:0.=:.::00:00 w: :5...:E0.5: 0.000 .0 :35 05.0 5.3 35.0000: 55:05:50 33 .500 ::0 5050.050: 0Z ”3.30m

 

5.. m.w~
85.0.5 . 0. .0w5: n..~ .Qm 050500w E0".
W00. .0 .0 :052 550500.00: :5. 530 .:0.m0.0..=0z 3. m. ”5%. mo... .50.: 0.505000 :5. 150.02 03“ 5005.2

 

0035.? 5:58:00 .0. 505.5. :0 .2... .0 0.0.0: 0.5.0 5095:0050
w: :5. 5502.5 :5. 00.000 .500 503.0: :52 53 50.5.0000: 500:5»: 02 m: :0..- 55.0.5 :. 02.0.05 50.. o. :08 5.3 0.05... :0>0m “00000.05 000.050. .0 0:0. .0 5:05.05: 5. .0
0.0... 0:... anon. :. 030:0. .0 0:0. 0.0.5.: .0 3....«555... 0.03 50.00.. w:.::=o.:00 .0. w:.:m=..:: .05: .0 0.0.0: 05.0 050090 3.02 .5505 5.3 3.5003: x..:a0c.:m.m mw:.::... 3:0 0:... .2500:

 

 

 

 

 

 

 

 

93. _fl .0 .500. 05528 . . . .05. _I 5.58 A :0 02.2.0
:0mmxm.:300v.02 .530 5050.050: 505303.. 50.0%.... 0mm 05:05 CON. ”50:: 5:02 :5. .:E0.:2 :3 505.02
.200. . I r :a :0 00.00.. :000200: 5.3 3.500%: . I. . 0.03 . m: :5. 0.5.: EU ”3.30m

80. b.0505 E00355 :5. 50:05:
.5 .0 53:50.0 5.500.553 50.50.... 50:05: .082 vwm 0:00» NE. 50.5. A $9. 5&5... 5:02 :0: 2.50 .mm :0~:E<

 

 

00:50... 5.0.080 5:002: 3033350200 «0 Engam .3 030,—.

 

138

   

 

 

..00. . 0=0=:...:00 . .. 530.08% ......n I ... .0m:..~_

08. ... .... 252 0.0 as... 05...... .005. H00.2 00> .00.... _ 03-3. 0.8. 0-0 0...... 0... .502 0.00580 ...... .25..ng o: _ 2.052
I 2.0.5.5200 .0. 2:00:00. 0:20 .0.05.000..m :0: .0...0.0 5.5%
......0.> 50500.03: 0wu=w03 .0. 0500...... :0 3.8. 0. 3.8. 50.. wig... 00...? ... 00.000 .28.. 5.3 3.0.0000: 003 00.3.5008”. m... 22.15.0055 .0w: .0 0.00» 0 ... :0 .... :030..0. 0:3 :0:00
0:. 5:3 ..movn: 0:0.» .958 0... :. 00.6.20 0:. .0 500.0... s. ......» :200500 ....00. 02.50.0000 .0 25.05.: .... :0: 0.5% 3.2»... 0.: :. 00.220 :.0 .00.. v 0.... .0 500.0. Nm ..rwon. 0:. :0 ”0.500:

 

 

 

 

 

 

 

 

 

 

 

 

 

   
   

0.00 0.0.9.500.
v :5. 0.0.500 :0....:0:.
.000. 0:020:00 :0:0.:5 0505
000. .0... 30.02200... 0.50 .5... .2020. 0 ...... 2.... 0.. 0.0....
...N .0 59.2.0.0. 0.03: .000 .50.). .000: 0.00.3 0: :0... . .o 00. 0.8. 0 2 ......
0.0.0500 R ....mN 0.05:0:00
:0...
0...... 3:00.05 5... EA 0020.. o. ...:0 ..:w2.. mm:
Om m:.:=.0:. .5... em... 0?... .000.» w... .:0:00.00
0%.. 500.0 .m... :30... cm .w: ..:w.:.. :. 5n... n... 5.05 5.... 0.02.05 ::...:0N
.... .0 5.52.0.0. 30.02052. .5825. .80.. ...000 .00.... 00 .... as. v ..A 0.. .. w 005.00 0.. 50...; :5. 350...: 08.... >32
.33.. 5:. 0.0: :. .0w:0..0. .5: 5:00.05 :. 000.502.0500 w: 000000.05 ...... .0:w.: . ... . 0:3 0... 00:0. 3000.05 .0 0000.03... 0:. .020 :5. 0w: .0 0.00. N :0.:..:0 w:05< 0.500:
000. P0505 :00: @5300 .:w.00: 5%. m.....:.N .0w::. .5050
.050 :5. 56.09 0.00.: $5005.03... .530 .00.w0.0.:0z — :3 0.00» 0 0. 05:05 0 — ”5.... :0 .::.:02 .5: 550.02 co: 20...... :05...

 

.8. .. .0."... 0:0..0..:00:00 w... :oo.:.:.00 :0000.0:. .0 5.50.9. :0..0>0....0..:=.. 50.055: .0. :0>.00:o 0.03 0.0.0: .:w..m 00.38 x0 ...02 .5000.
:..3 3.0.0000: ......a0....:m.0 .0: 0.03 0.0.50.2. :00.0>0..:=0.> :5. 022.002. 50.8.... .b.>...0:00 00.500 $.50: .::0.> 05:05 0 0. v .0 0.0.0: .00.m0.0:0>0..0.=0: 2:3 3.0.0000: 0:3 :0..:..:00:00
w: :.00 0. 0000.00. :.0..o. : :2. 0.02.3 0.0.:w..00>:.. .0w: .0 0.00.. .. :0.:..:0 :. .3530. .03.: .0 0.00..0 5.2.000: 0:. w:..00ww=0. 5050320.. :5... 0.05 ......» :0: 0m: .0 05:00.. N. ... :0.:.20
0. 0.5.5.5350 m... .5: 0:»... ...0: ....3 3.0.0000: 0:3 m:.0...z 05:05 N. ... :0..:::00:00 w... ...... 0.00:0.20 .05. 5050.020: ... 0w: 0003.0: :55. 055 00.5.0000: 00.0>:. .::0...:m 0 < .0..=00~.

 

.530
...0.w0.0.0»:..0.:0: .530 E050::..E... 5.... «AN .:...02 0... .. .5: 220
% 30000.0 ....>...0:00 .0358 5... N... 5002 :05 N. :0: 220
30. .00: 5.30 .....0.> ...Umu .m2n.<z 5.... m... 5:02 :0: 55.0.02
.... .0 5.0.3500 ....Zm .U.....>U .0.: £093 ...... .32 :0 0.00.. .- ...m: 0.NN .502 :02: :50
30. ..0:0 .00» wisp. 5.... ......eN 0mg. 0:5..0.
.... .0 502:5... 0000.025. 550500.030 mmn 0305.05. 15.0.02 .50.. m... .0005 0.505000 :0: ......052 NNo.. 00.0..

 

 

.09. 00.50% :. :0. 03.0. 0.003... a .0 .: 0.9.0.00 0:. .... 5 3.0.0000:
003 m... :02: :.00 :. 00:20:. 20.6. a. 52.550008 w... :00.:-0.0:3.:.00 :5. 00.000 5:05.30 5050.050: 0003.0: 020:0:30. 00.0>:. 0.: 0:3 0008......00 .0 03000.30. 2:0 0:... ”0.500:

 

...»: EVE. 0M5.

 

 

 

 

....w: mN .5005 0.505000 50.0w :.0U
......
8.0.. 005: ...... ...... as: 08... .050
:8. 00.. 2803000 .0. E... 0.0. 85...
.... .0 203.03% 5.3.0 .00.m0.0....0z Nm. .0. :30: _.:0 00.00... N yen. .0m:~. .50.. me: .032 :0: .0E0...2 N... 00...".

 

 

 

 

.0585 cc ... ....n. m... :5. .50.. m. 003 05:05 0 n :00 o. .0:
... ..0:00 05 .0. ...<02 05. 0.50.05 0. 0.000....0 300.00.. .0 25:0... :5. w::...... .0 w:.0..03 .0. 00:202.... .5:0E...0.0>0: 0:. .0 5050320.. .0. 00m: 0:. 503.0: :55. 003 5.5.0000: 02 00.5: .0.

 

3N Om. 0:505 o.. . :50 00.500. .0. GNHGMV 0220... m6. 0.03 m:..=~. .0. 0w: 0:05 0:... 00.00. .0. SNHOm. 05:0... 0.0. :5. 00.500. .0. 3.. Om. 05:00.. 50. 0:3 w:..=§> ... 0.0.: :00... 0:... “0......03.
.50/.714 ..................:.:.. ....4...::c.: 0:1. ......I.
.. ...—1...... u n: ......._.\..I.._ ... I. ...:727... ......1... ......T,

 

 

        

   

 

 
   

2...... ...... .50/.05).

 

     

139

fine-58¢ v9.0.1". 32> flu?» ”mom—5%“;— nox0>m 5:23 ESE—Em (Hafi— uwogw coo—2 me 2:05 Ewe—22,

323.52 def—<2 58,—. mEEaZ Eamon Hz: 52220 I so... wig _~£o> «ESE—«U UAW—>0 ”Emma“. :83 v5 665835... .Sam :33 @833. I Era—EU .8 28m oucowEBE .6280?
.1693 an»... occur—totem =3.an .E 58. uoaantotoa 39.380 25 .Suuanzoon. "$0652 $59.5 Baum: Eammm SEE—gm _§_>Eono.aoz .92 A8328 0396." BE E83 238:0
.2228 EEO Juno ”3:5“ _a=~%-_§m_>v 30,—. =u.80-._uv=om .0.: ”8:085th 3080353. ..o 38,—. nomgqiooouSB 9: mo .853 2.9395 3:3.“ .mfiflr?» 532 9.68: 525353 mo
33% =85§$8uuoo>> 2: we .85.; 2.2—$80.. 203-882 .EAEFDS ”3939:“. 03332 was 0:32.:3 28w nus—was .858: W: ”CE—Ba claims Evauwv BEE? @5520 ..o 8.8m
3:592 {Um—2 ..EoEaeuSQ :5:— _o mufiuw .315 .92 ”Snowing:— 255 Mo zap. Swan i=1.— ..Eoi? 325.. a a. gunman: .noh wuioobm 35.5235 .932“. Ema: M:o=£>2£<

 

.quEoo 329:: .3203 2: can 9:»: @263
2: ho 7.52 2: E w: ,8 “out“. ca 53> :55ng 82> 958 293633 05 .vuguutncz Ego—5m v.53 r558 06 E 3:53:3— mcouflauocou w: 803 ES 363m 3503:; 2: sm=o§< 6:3;

 

Am==Ua
as: $2 H23% 23:8 an 52229
£5. .__.. z 5:55 mm; 223:: 8.58:8 2.2 25 3-2 Ea 2a N55:5 x s 90 is n: .532 82m “5 3 538m

 

 

a EBOQ on>o._a=m_> was .3228 @333 DEE—a E2255 E 86:22 5;; 3.3.53." mu? m: :n..._aEBa—2 “mg—smog

. L.

 

boEoE EBA H_u=_m.c._ot=5m

 

 

 

53% .483 5% :3 ”mom;

140

Neurological Status

Overall, the evidence that children’s neurological status is associated with low-dose

chronic prenatal Hg exposure consists of the following findings:

Abnormalities of muscle tone or reflexes in boys is significantly associated with
prenatal MeHg exposure, though the effect is not dose dependant (the risk of an
abnormality of tone or reflexes increased seven times with each 10 ppm increase in
maternal hair Hg) (McKeown-Eyssen et al. 1983),

There is a significant inverse relationship between newbom’s neurological optimality
scores and cord-whole-blood Hg concentration (a lO-fold increase in cord blood Hg
was associated with the equivalent of a 3-week reduction in gestation age.
Adjustments for total PCBs and fatty acid concentrations had no effect on results.
Mean Hg concentration was 20.4 ug/L) (Steuerwald et al. 2000),

7-year old children who performed sub-optimally on a finger opposition test had a
modest but statistically significantly higher mean Hg cord blood concentration than
children with optimal performance (23.9 versus 21.8 ug/L, p=.04) (Grandjean et al.
1997), and

Among a cohort of children 9 months to 6 years of age, an association between
increased reflexes and higher Hg concentrations in maternal hair for children greater

than 2 years of age (stronger in boys than girls) (Cordier and Gare] 1999).

Age at Achievement of Developmental Milestones

Recent epidemiological studies provide little evidence of an association between maternal

hair mercury below 30 ppm and delayed developmental milestones. Although the main

141

cohort Seychelles Island Development Study (Myers et al. 1997) found that there was an
association between age at walking and matemal-hair mercury in boys, Axtel et al.
(1998) found that the mean age of boys at walking increased (only slightly) as matemal-
hair Hg increased from 0-7 ppm, but decreased from beyond 7 ppm. Therefore, the risk of
delayed walking did not appear to be dose related because the size of the effect was small

(less than one day) and the association was nonlinear.

Age of achieving developmental milestones was studied by Grandjean et al. (1995) in a
21-month birth cohort of 1,022 infants in the Faroe Islands. The indexes of prenatal Hg
exposure used included matemal-hair Hg concentrations, infants’ umbilical cord blood,
and children’s hair samples obtained at about one year of age. Endpoints that are
commonly achieved between five and 12 months were selected to measure motor-
developmental milestones and included sitting without support, creeping, and getting up
into standing position without support. Complete data was available for 53 percent of the
cohort (583 infants). No significant association was found between the age at
achievement and either index of prenatal exposure, but a significant association was
found between age at achievement and postnatal exposure (children’s hair). Nursing was
found to cause higher hair Hg concentrations in children and more rapid achievement of
milestones, which suggests that the beneficial effects of nursing on early motor
development are sufficient to compensate for any slight adverse impact that low-dose

prenatal MeHg exposure might have on the end points.

142

Infant and Preschool Development

There is some indication of low-dose mercury effects in very young children, but there
are difficulties in the measurement of such effects. There are many standardized tests
widely used in epidemiological studies to assess the association between low-dose
prenatal MeHg exposure and early child development. The Denver Developmental
Screening Test (DDST) was used in four different studies (McKeown-Eyssen et al. 1983;
Kjellstrom et al. 1989; Myers et al. 1995a and b) to measure infant development. Of
those, the New Zealand and Seychelles pilot phase studies revealed an association with
prenatal Hg concentrations and children’s scores when questionable and abnormal
findings were combined (Kjellstrom et al. 1989 and Myers et al. 1995b). The differences
between the findings of these four studies could be due to the diversity of ages at which
the tests were administered, the different rates of abnormal or questionable examinations,
test administration differences, or the use of different criteria to judge results (NRC

2000).

A different test, the Bayley Scales of Infant Development (BSID), was administered to
children in the Seychelles main cohort and yielded two primary scores: the mental
development index (MDI) and psychomotor development index (PDI). The MDI scores
(97.5 and 100.4 at 19 and 29 months respectively) were similar to the expected mean for
US children of 100 t 16. The PDI scores at both ages, though, were markedly higher
than the expected mean for US. children; approximately 200 Seychelles children at 19

months achieved the highest possible score (Davidson et al. 1995).

143

The BSID is recommended as a better infant assessment tool than the DDST because the
DDST is not sensitive to variations within the range of normal performance, and the
BSID is sensitive to prenatal exposures to a variety of neurotoxicants like lead and PCB’s
(NRC 2000). Among the mercury studies that have assessed infant development, only the
Seychelles main study (Davidson et al. 1995) administered the BSID, and no significant

associations were found between children’s scores and their prenatal exposure.

Childhood Development

There is ample evidence of low dose in utero mercury effects on neuropsychological
indices in school-age children, particularly in the domains of attention, fine-motor
function, confrontational naming, visual-spatial abilities, and verbal memory. The Faroe,
New Zealand, and Seychelles pilot study reported significant inverse associations

between neurodevelopment and MeHg.

In the Faroe Island cohort (Grandjean et al. 1997), a battery of neuropsychological tests
was administered at 7 years of age to 917 of the surviving members of the 1,022 cohort.
Increased cord-blood Hg concentration (mean, 22.9 ug/L) was significantly associated
with worse scores on finger tapping (preferred hand, p=.05), continuous performance test
in the first year of data collection (false negatives, p=-.02; mean reaction time, p=.001),
WISC-R digit span (p=.05), Boston Naming Test (no cues, p-.0003; with cues, p=.0001),
and the California Verbal Leaming Test — Children (short-term reproduction, p=.02;
long-term reproduction, p=.05). Investigators estimate that a lO-fold increase in cord Hg

concentration was associated with delays of 4 to 7 months in those neuropsychological

144

domains. Most test scores were more strongly associated with cord-blood mercury than
with maternal hair mercury. In the case-control portion of the study, the case group

scored significantly lower than the control group on 6 of 18 endpoints.

In the New Zealand cohort (Kjellstrom et al. 1989), at age 6, matemal-hair Hg
concentration in the high-Hg group (mean, 8.3 ppm) was associated with poorer scores
on full-scale IQ, language development (spoken language quotient), visual-spatial skills
(perceptual-performance scale), and gross-motor skills (motor scale) (p = .0034 - .074).
The poorer mean scores in the high-mercury group were largely attributable to the

children of mothers with hair mercury above 10 ppm.

Among the 271 66 month-old subset of the Seychelles pilot cohort (Myers et al. 1995c)
of 789, matemal-hair Hg concentrations (median, 7.1 ppm) were associated with
significantly lower general cognitive index scores (p=.024), Preschool Language Scale
scores (p=.0019), and perceptual-performance scale scores (p=.013). Because this study
was for feasibility purposes, no information was collected on socioeconomic status,
caregiver intelligence, or quality of home environment. The Sychelles main study did not
report such associations. In the main Seychelles study (Davidson et al. 1998), the pattern
of scores on six neurodevelopmental end point tests administered to the 66 month-olds
did not suggest an adverse effect of either prenatal (mean: 6.8 ppm) or postnatal (mean:

6.5 ppm) Hg exposure.

145

Effects of mercury exposure were also observed in two smaller populations. A recent
study indicated that the majority of hair mercury levels in Indian and non-Indian women
and children within the Amazon Basin are in the range of 10-20 ug/g (ppm), within range
of the threshold indicative of adverse effects to fetal development (Barbosa, Silva, and
Dorea 1998; Clarkson 1992). Levels in general were higher in non-Indian subjects, which
are estimated to consume more fish (contaminated by upstream gold-mining activities)
than the Indian population (Barbosa, Silva, and Dorea 1998). Grandjean et a] (1999)
found that children’s hair mercury concentrations were significantly associated with their
scores on finger tapping, dexterity, and digit span tests. Also, in a French Guiana cohort,
it was shown that maternal hair mercury was associated with low copying-design scores

(more so in boys) (Cordier and Gare] 1999).

Sensory, Neurophysiological, and Other End Points in Children

There is increasing evidence of adverse endpoints other than cognitive development in
mercury-exposed children. During the 7-year evaluation of the Faroe Islands study
(Grandjean et al. 1997), there were delays in some auditory-evoked potential peaks as a
function of cord-blood mercury. Similar findings were reported in a cross-sectional study
of 149 6- to 7-year old children living in a fishing village on Madiera (Murata et al.
1999). A relationship was also found between blood Hg concentrations and auditory

function in the right ear at 3kHz in children and adults in Ecuador..

Comparison of Studies

146

Several epidemiological studies have evaluated subtle endpoints of neurotoxicity in an
attempt to establish response relationships to low-dose MeHg exposure (see Table 16).
These studies are important in that, unlike the acute poisoning episodes in Japan and Iraq,
they relate more to levels of exposure in the United States and, therefore, are more

appropriate for use in risk assessment.

The three largest and most comprehensive epidemiological studies were conducted in the
Faroe Islands and the Seychelles Islands (main phase). The Faroe Island cohort examined
the correlation between neurodevelopmental criteria in children and methylmercury
exposure indicators, including maternal hair and placental cord blood. The setting for this
study was the Faroe Islands (part of Denmark, located in the North Sea between Scotland
and Iceland), a small Nordic community of approximately 45,000 inhabitants. Seafood
consumption in this community is highly variable, and the population is socially
homogenous. A major component of seafood consumption is the meat of the pilot whale.
Deficits in speech, attention, and memory in seven-year olds were correlated with the
methylmercury exposure indicators. Placental cord blood was the strongest predictor of

these effects (Grandjean et al. 1997).

The Seychelles Island main cohort study examined the neurodevelopmental effects of
pre- and post-natal methylmercury exposure in children. The setting for the study was the
Republic of Seychelles, an archipelago in the Indian Ocean off the coast of East Africa,
where 85 percent of the population consumes marine fish daily. A battery of five

developmental tests was administered to 711 children in the cohort at 60 (+/— 6) months

147

of age. Pre and post-natal exposure levels, as well as a number of other factors (diet,
parental I.Q., sex, medical history, etc.) were analyzed to explain the outcomes of the
developmental tests. No deficits were found resulting from Me-Hg exposure; the
outcomes of the tests were explained largely in terms of the alternative factors. In some
instances, performance on the tests improved at higher levels of Me—Hg exposure. The
authors speculate that this may result from the beneficial aspects of fish consumption,
including omega-3-fatty acids, and so the benefits of consuming fish may outweigh the

health risks (Davidson et al. 1998).

Although the exposure in both studies was similar, different conclusions were reached.
The Faroe Islands study found a range of adverse neuropsychological and
neurophysiological effects associated with prenatal Hg exposure, but the Seychelles
Island found none‘. Explanations for these discrepant findings have been offered (see
NRC 2000). In general, possible explanations include the following issues:

0 Influences of confounders and covariates: Although neither the F aroe nor the
Seychelles study controlled for all potential confounders, the NRC (2000) concluded
that both evaluated most of the control variables that could have confounded
associations observed between exposure and outcome. A few control variables that
are sometimes modestly related to childhood neurobehavior were assessed in one
study and not the other, including maternal age and birth order in the Seychelles study
and obstetrical care in the Faroe Study, but the influences of those variables are

probably too weak to account for any major inconsistencies between the two studies.

 

‘ An association was found between age at walking and matemal-hair mercury in boys (Myers et al. 1997). but was later found to be
non-linear (Axtel et al. 1998).

148

Other possible confounding issues include place of Faroese residence (town versus
country), test administration (examiner was not controlled for in the Seychelles
study), age at testing, exclusion of Seychelles individuals with severe impairments,
and PCB exposure in the Faroese population.

Population difl’erences in susceptibility: Susceptibility to effects of a toxicant can
depend on predisposing factors, such as nutritional status, exposure to other agents, or
genetic susceptibility. Genetic susceptibility is at issue here, because the Seychelles
cohort was predominately African in descent and the Faroes cohort was Caucasian.
Timing, extent, and frequency of exposure: Exposure to MeHg in the Seychelles is
though daily consumption of fish (continuos exposure), as opposed to the Faroese
whose significant source of MeHg is pilot whale meat consumed relatively
infrequently (episodic exposure).

Biomarker differences: To assess prenatal mercury exposure, cord blood and
maternal hair concentrations were measured in the Faroe study and only maternal hair
mercury in the Seychelles. Also, the maternal hair mercury samples collected in each
study did not reflect the same period of pregnancy.

Differences in assessment batteries used: Both studies used different
neurobehavioral test batteries. In addition, the age of the children assessed in both
studies was different; 7 year olds in the Faroe Islands and 5.5 years in the Seychelles.
Biostatistical issues: Because the magnitude of the association between mercury
exposure and expression of neurotoxicity is subtle, it is not likely that the association

will be detected in every cohort studied. The differences between the two studies

149

could simply be due to sample variability in the expression of neurotoxictiy at low

doses.

The completion and peer review of the New Zealand study helped to resolve some of the
issues noted above. In the New Zealand study, the population’s sources of MeHg were
similar to those examined in the Seychelles. Children at 4 and 6 years of age who had
been exposed in utero to MeHg were given a battery of neuropsychological and
neurophysiological tests. As was the case for the Faroe study, decrements were reported
in test performance at both ages in the children exposed prenatally to moderate high
doses, including four endpoints that were found to be unrelated to MeHg (Crump 2000).
Differences between the Fareo and Seychelles studies regarding the primary biomarker of
Hg exposure, type of neuropsychological tests administered, age of testing, and sources
of exposure (whale meat versus fish) no longer seemed determinative after the New
Zealand study results were examined. Although exposure and research design were
similar between the New Zealand and Seychelles studies, associations between MeHg
exposure and and worse neurobehavioral test scores, as did the pilot phase of the

Seychelles study (NRC 2000).

Tests preformed by Grandjean et al. (1997) to ascertain if the PCB and mercury effects
among the Faroese could be separated revealed that it is not possible to determine the
relative contribution of each. The NRC (2000) concluded that there is no empirical
evidence or hypothesized mechanism to support the suggestion that PCB exposure might

have enhanced the Faroese’s vulnerability to MeHg. Statistical tests for interaction

150

between PCB and mercury showed no interaction. It is unlikely that a difference in PCB
exposure between the Faroes and Seychelles populations explains the lack of
developmental neurotoxic effects in the Seychelles, where PCB body burdens are very

low.

These are some of the factors that may account for the finding of adverse outcomes in the
Faroes and New Zealand studies and the lack of them in the Seychelles, but non of them
represent a critical flaw in any of the studies, nor do they adequately explain the
differences (NRC 2000). After careful review, the NRC chose to recommend the study of
neurotoxicity in 7 year old children in the Faroe Islands as the critical study on which to
base MeHg exposure standards (RfD). The EPA has concurred with this finding. The
advantages of this study over the others include a larger sample size, the use of two
different biomarkers of exposure, and extensive peer review. The Seychelles study shares
many of the strengths of the Faroes study, but the NRC (2000) concluded that a positive
study is the strongest public health basis for and RfD. Disadvantages present in the New

Zealand study included a small sample size and limited peer review.

ECOSYSTEM AND WILDLIFE IMPACTS

Mercury has a wide range of harmful effects on wildlife. Transported to ecosystems
from a sources such as atmospheric transport (wet and dry deposition), runoff from storm
events, and direct discharge to water bodies from industrial effluents, mercury is
absorbed by organisms from the air, water, and soil, as they eat, drink and breathe.

Mercury absorbed from food accumulates in the organism’s body and damages the liver,

151

kidneys, and especially the central nervous system. While much work in assessing the
effects of environmental mercury to human health as centered on the issue of mercury as
a neurotoxicant, studies in wildlife have focused on the reproductive effects of
environmental mercury. Its effects are most devastating in embryos and the young, and
mercury is suspected as an important cause of reproductive failure among loons, eagles,

mink, turtles, river otters, and other wildlife across the US.

Figure 26: Mercury blood levels in common loon (Evers et al. 1998)

 

Mercury Levels in the Common Loon

&

 

l
l

 

(A)

N
or

 

.5
0|

‘
1

AverageMercurylnLoonBlood(ug/o)
M

.0
or

 

 

 

0

Alaska Pacific Northwest Upper Great Lakes New Endand Canadian Maritime
Provinces

 

 

 

Since methylmercury is biomagnified throughout the food chain, animals at the high end
of the food chain accumulate the highest levels of mercury. These animals include
predatory fish, predatory mammals, marine mammals, and predatory birds. Predatory
birds that consume fish such as Ioons and osprey are also at risk, because mercury is

prevalent in aquatic ecosystems, and readily bioaccumulates in fish.

152

Researchers have found that mercury concentrations in loans tend to increase with age,
and that mercury levels increase generally from west to east across North America
(Evers, et al, 1998). Loons in Alaska, for instance, have only about 0.66 ppm of mercury
in their blood compared to levels in the Pacific Northwest, which averaged 1.7 times
higher (1.1 ppm), 2.4 times greater in the upper Great Lakes (1.58 ppm), 3.5 times greater
in New England (2.3 ppm), and 5.3 times greater in the Canada’s Maritime provinces, an
extremely high 3.5 ppm. This trend reflects the US. EPA prediction model of total

anthropogenic mercury deposition across the United States. (Evers et al. 1998).

In Maine, mercury poisoning in loons has caused reproductive problems and has limited
their ability to fight off disease (Bradbury, D. 1997). Furthermore, acid rain appears to
compound the mercury problem, since acidification increases the solubility and mobility
of mercury and other toxic metals. Researchers in Wisconsin, for example, have found
elevated levels of methylmercury in loons nesting on acidified lakes, as compared to
those that nest on less acidified waters (Meyer, M.W 1995). Also, mercury levels
associated with reproductive impairment and toxicity were recently reported for
emaciated loons found dead or in a weakened state in eastern Canada, and these levels
were higher than in apparently healthy loon (Scheuhammer, A. M., et al. 1998).
Additional research has observed apparent mercury-related effects on behavior of young

loons that may effect their survivability (Nocera, J. J. and PD. Taylor 1998).

Other fish-eating waterfowl are affected as well. For example, moderately high levels of

mercury have caused reduced hatching success and duckling survival in mallards and

153

American black ducks (Zillioux, E]. 1993). Sampling and analysis of Great Lakes
Herring Gull eggs between 1973 and 1992 revealed that in general, herring gull eggs
mercury levels were highest in 1975 and 1982 (Koster, MD. et al. 1996). Mercury
burden in these eggs slowly declined and leVeled off in the late 1980’s and early 1990’s.
This finding indicates that mercury levels will likely not decrease further until

anthropogenic mercury discharges to the environment are reduced.

During the 1970’s, the mercury burden in Great Lakes Herring Gull eggs varied, with the
highest levels being found in Lake Ontario and Lake Superior. This trend paralleled
mercury levels observed in rainbow smelt, a common food source of the gulls. Spatial
variation may indicate variation in loading to the lakes. The long retention time of Lake
Superior may result in long retention times of toxins. By the early 1990’s, mercury
burdens were more evenly distributed across the Great Lakes. This may be the result of a
shift from point source loading of mercury to diffuse, non-point sources (especially

atmospheric deposition).

In addition, high mercury levels have been identified in free-roaming Florida panthers,
especially those with a diet rich in raccoons, rabbits, armadillos, and alligators (Roelke,
M.E. et a1. 1991). Scientists now think that chronic exposure to mercury may be partly
responsible for lower than expected population densities of panthers in much of their
range and may actually be contributing to the extinction of these highly endangered

animals.

154

APPENDIX II

PHASE I CONSENT FORM

Date

Name
Address
City, State Zip

Dear

 

The purpose of this letter is to ask for your participation in the study “Mercury Emissions
from Coal-Fired Power Plants: A Critical Analysis of Reduction Strategies.” This study is
being conducted to address an important environmental policy issue (i.e. coal-fired utility
mercury emissions) and to fulfil the thesis requirement of a Master of Science degree in
Resource Development from Michigan State University.

Explanation of Research

Mercury emissions from the coal-fired utility sector pose a challenge for the condition
our rivers, lakes and streams, as well as the health of people and wildlife that depend on
these waterbodies for food, habitat, recreation, and enjoyment. This study will contribute
to the ongoing public policy debate regarding whether mercury regulation for the coal-
fired utility sector is needed, and if so, what emissions management strategies should be
adopted.

Research Procedure

You are being asked to participate in this study because of your expertise and experience
regarding the research problem. If you consent to participate, you will be contacted
twice:

1. I will contact you by phone for a one-hour phone interview (please select a
date and time that is convenient from the choices below). The telephone
interview will cover the following topics (a) possible mercury reduction
strategies, (b) criteria for evaluating these strategies, and (c) policy ideas for
implementing these strategies.

2. Several weeks later you will be mailed a written survey based on the results of
the telephone interviews. You will be asked to evaluate a number of
alternative mercury reduction strategies, criteria, and goals. This survey will
contain approximately 30 questions and should take no longer than one-hour
to complete.

Assurance of Confidentiality

All data gathered during this study will be treated with strict confidence. Your
confidentiality will be protected to the maximum extent allowable by law and, to ensure
confidentiality, your identity will only be known to my advising professor and me. Any
reports of research findings that result from this study will not associate your identity
with specific responses or findings.

Consent to Participate

Participation in this study is voluntary. You may choose not to participate at all, may
refuse to answer certain questions, or may discontinue participation at any time. If you
freely consent to participate, please sign below and mail this entire document to me
in the envelope provided.

 

 

Signature Date

 

Name

If you have any questions or concerns regarding your participation in this study, please
contact:

Julie C. Metty

Principal Investigator

131 West South Street

Williamston, MI 48895

517/484-4954 (day)

517/655—6254 (evening)

mettyjul@msu.edu

If you have questions about your rights as a human subject of research, please contact:
David E. Wright, Chair
Committee on Research Involving Human Subjects
Administration Building University
Michigan State University
East Lansing, MI 48824-1046
517/355-2180

Thank you,

Julie C. Metty
Principal Investigator

156

APPENDIX III

PHASE II CONSENT FORM

 

 

IMPORTANT INFORMATION
PLEASE READ BEFORE ANSWERING THE QUESTIONNAIRE

The purpose of this survey is to identify priority strategies that could be used to control mercury
emissions from coal-fired power plants, reflecting the perceptions and values of experts from
diverse constituencies. I would appreciate your taking the next 30-45 minutes to complete the
attached questionnaire.

Participation in this survey is voluntary. This means that you may choose not to participate at all,
you may refuse to answer certain questions, or you may discontinue completing the questionnaire
at any point.

Consent Statement: You indicate your voluntary agreement to participate by completing and
returning the questionnaire.

Data gathered for this survey will be treated with strict confidence on the part of the research
investigator. The names of subjects will not be linked to responses and subjects will remain
anonymous in any report of research findings. Your privacy will be protected to the maximum
extent allowable by law.

Should you have any questions or concerns about this study, please contact:

Julie C. Metty, Principal Research Investigator
Michigan State University

131 West South Street

Williamston, MI 48895

ph: 517/484-4954 (day), 517/655-6254 (evening)
mettyjul@msu.edu

Questions pertaining to a participant’s rights as a human subject of research should be directed to:

Dr. David Wright, Chair

University Committee on Research Involving Human Subjects
Michigan State University, Administration Building

East Lansing, MI 48824-1046

ph: 517/355-2180

Your assistance in this research is very much appreciated.

Julie C. Metty
Principal Research Investigator

 

157

 

APPENDIX IV

PHASE II SURVEY INSTRUMENT

November 21, 2001

«Saluation» «First_Name» «Last_Name»
«Organization»

«Addressl»

«AddressZ»

«City», «State» «Zip»

Dear «Saluation» «Last_Name»:

You have received this survey because you have been identified as an expert, who can provide valuable
information for the study, “Mercury Emissions from Coal-Fired Power Plants: A Critical Analysis of
Reduction Strategies.” This study is being conducted to address an important environmental policy issue
(i.e. emissions management of coal-fired utility mercury emissions) and to fulfil the thesis requirement of a
Master of Science degree in Resource Development from Michigan State University.

Explanation of Research

Mercury emissions from coal-fired power plants pose a challenge for the condition of our rivers, lakes and
streams, as well as the health of people and wildlife that depend on these waterbodies for food, habitat,
recreation, and enjoyment. This study will contribute to the ongoing public policy debate regarding what
type of emissions management strategy should be promulgated by the US Environmental Protection
Agency to address mercury emissions from coal-fired power plants.

Over the past two months, experts from the utility sector, government agencies, and environmental
organizations have been interviewed to explore the different strategies that can be used to control mercury
emissions from coal-fired power plants, as well as the different criteria that can be applied to evaluate these
strategies. These interviews revealed six alternative mercury emissions reduction strategies and nine
possible evaluation criteria. These strategies and criteria h ave been incorporated into the attached survey
and distributed to a broader group of experts from the same stakeholder groups, of which you are apart.

The purpose of this survey is to learn (a) your preferred strategy for controlling mercury emissions from
coal-fired power plants, (b) the relative importance you place on each criteria when evaluating different
mercury emissions reduction strategies, and (c) your preferred strategy with respect to each individual
criteria. Once collected, this information will be analyzed to identify priority mercury emissions reduction
strategies reflecting the perceptions and values of experts from diverse constituencies.

Please complete the attached survey and return it to me by April 17'“, 2001 in the postage-paid envelope
provided. Thank you in advance for your help with and support of my research endeavor.

Sincerely,

Julie Metty
M.S. Candidate/Principal Research Investigator
Michigan State University

158

Thank you for taking the time to complete this survey. Please indicate to which organization/sector you
belong (check one):

[3 Utility Industry
D Government Agency

B Environmental Organization

SECTION A: Banklng of Alternative Strategies

1. Please rank the following six mercury emission reduction strategies, assigning l to your most preferred
strategy and 6 to your least preferred strategy. Please assign a different number between land 6 to
each strategy, using all numbers:

Maximum Achievable Control Technology (MACT) numerical emission limit: EPA
determines MACT emission limit and leaves the choice of control technology to the utility

industry.

MACT technology regulation: EPA determines MACT emissions limit and promulgates a
technology standard for the utility industry.

MACT numerical emission limit plus emissions trading: EPA determines MACT emission
limit and leaves the strategy for compliance up to the utility industry including emissions
trading. -

Mum-pollutant regulation: EPA establishes and promulgates emission standards for
multiple pollutants (e.g. NO," C02, 802, and Hg) at one time.

Receptor-based emissions limits: EPA establishes and promulgates mercury emission
standards for single plants based on their specific and identified pollution contributions.

Risk-based emissions limit: EPA establishes and promul gates a mercury emission standard
for the utility industry based on the estimated risks to the human population and ecosystems,
i.e., the standard would provide an ample margin of safety to protect public health and
ecosystems.

159

SECTION B: Criteria Importance Ratings

The following are nine criteria that might be used to evaluate the six alternative mercury reduction
strategies described in Section A.

 

Criteria Definition

Effectiveness The ability of the reduction strategy to reduce mercury to target levels
Economic feasibility Impact on business viability and power reliability, i.e. the reduction strategy’s
impact on utility operations, generation capability, company logevity, etc.
Technological Need for new technology, i.e. the reduction strategy requires additional
feasibility technological innovations.

Compliance flexibility Amount of industry latitude in seleiing a reduction method/ technolgy
Planning certainty Level of certainty regarding future pollutant regulations and pollution control
needs

Political feasibility Level of political constraints in implementing the reduction strategy
Scientific defensibility level of scientific certainty associated with the reduction stratea

Legal feasibility Need for new or modified laws, i.e. the reduction strategy requires additional
legal mechanisms.

Cost-benefit Degree of benefit compared to cost

 

 

 

 

 

 

 

 

 

 

 

 

 

This section of the survey asks you to compare the relative importance of the above criteria in evaluating
the alternative mercury reduction strategies. Using the importance scale provided, you will be asked to
make a series of pairwise comparisons and indicate the relative importance of the nine criteria in evaluating

the six alternative mercury reduction strategies.

The following is an example of a pairwise comparison using the hypothetical goal of purchasing a laptop.
computer.

 

Example

Goal: Purchasing a laptop computer.

Evaluation criteria: Criteria 1 — Price ( cost of the laptop)
Criteria 2 - Memory (size of hard drive)

Pairwise comparison: Using the scale below indicate the relative importance of
the two criteria (price and space) with respect to the goal: purchasing a laptop

computer:

 

Criteria
1 Criteria
2

Memory

‘0 Extreme

 

 

 

9° Moderate
Strong
‘1 Very Strong

U!
a

\1 Very Strong

\0 Extreme
as

00

r.» IModerate

N

Ur Strong
#- l

H Equal
N

Price 4

 

 

 

In this example, the respondent is saying that price is moderately to strongly
more important of a criteria than memory when purchasing a lap top computer.

 

 

 

160

I. For each item below (i.e., a, b. c, etc.). using the scale provided please indicate which of the two
criteria is more important with respect to achieving the overall goal: reducing mercury from coal-
fired power plants. Circle the number that represents the relative importance of the criteria.

Note: For each pair of criteria (i.e. a, b, c. etc) below, only one scale value should be circled.

 

Criteria 1

Economic feasibility: Technological feasibility:
impact on business 3 4 5 6 7 8 9 need for new technology
viability and power

reliabilit .

Compliance

flexibility: amount of

industry latitude in

selecting a reduction regulations and pollution
control needs.

Poallitic feashibity:
level of political
constraints.

galfeasibility: 9 8 7 6 5 4 3 2 l 2 3 4 5 6 7 8 9 Cost-benefitzdegreeof
nwd for new or benefit compared to cost.
modified laws.

 

161

SECTION C: Strategy Comparkons

In this section of the survey, for each evaluation criteria (e.g. effectiveness), you will be asked to indicate
your preference between a pair of alternative mercury reduction strategies. As in the previous section, this
will involve a series of pairwise comparisons.

1. Criteria: Effectiveness
For each pair of strategies, using the preference scale provided, please indicate which strategy is preferred
with respect to the criteria effectiveness (the ability to reduce mercury to target levels). For each item
below. circle the number that represents the level of relative preference with respect to the criteria. Note:
For each pair of strategies, only one scale value should be circled.

 

a
g g SrraregyZ
g a

. . t “wk . - a

MACT technology MACT numerical

regulation: EPA emission limit plus

determines MACT 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 emissions trading: EPA

emission limit and determines MACT

promulgates a Criteria: Effectiveness emission limit and leaves

technology standard for the strategy for

the utility industry. compliance up to the
utility industry including
tradilL.

Mum-pollutant Receptor-based
regulation: EPA standard: EPA
establishesand 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 establishesand
promulgates emission promulgates emission
standards for multiple Criteria: Effectiveness standards for single
pollutants (e.g. NOx. plants based on specific
C02. 802, and Hg) at pollution contributions.

 

162

2. Criteria: Economic feasibility

For each pair of strategies. using the preference scale provided, please indicate which strategy is preferred
with respect to the criteria economic feasibility (impact on business viability and power reliability). For
each item below, circle the number that represents the level of relative preference with respect to the
criteria. Note: For each pair of strategies. only one scale value should be circled.

 

M
t:
O
Strategy1 g 5: m
g E

emission limit and Criteria: Economic feasibility

P10 emission limit and

mulgates a
technology standard for leaves the strategy for
the utility industry. compliance up to the
utility industry
includin tradin

d. Multi-pollutant
regulation. EPA
establishes and establishes and
promul gates emission promulgates emission
standards for multiple
pollutants (e.g. NOx.

 

 

163

3. Citeria: Technological feasibility

For each pair of strategies, using the preference scale provided, please indicate which strategy is preferred
with respect to the criteria technological feasibility (current technological availability). For each item
below, circle the number that represents the level of relative preference with respect to the criteria. Note:

For each pair of strategies, only one scale value should be circled.

 

Strategy 1

Moderate
Strong
Very Strong

Equal

Very Strong

Extreme
Strong
Moderate

MACT technology MACT numerical
regulation: EPA emission limit plus
detemiinesMACT 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 emissionsu’adinngPA
determines MACT
Criteria: Technological feasibility emission limit and
leaves the strategy for
compliance up to the
utility industry
includin_ tradin_.

emission limit and
promulgates a
technology standard for
the utility industry.

Wl-polltan
regulation: EPA
establishes and

promulgates emission
standards for multiple Criteria: Technological feasibility standards for single

98765432123456789 establishesand
promulgates emission

plants based on specific

pollutants (e.g. NOx,
pollution contributions.

C02, S02. and Hg) at
one time.

 

Criteria: Compliance flexibility

For each pair of strategies, using the preference scale provided, please indicate which strategy is
preferred with respect to the criteria compliance flexibility (amount of industry latitude in selecting a
reduction method/ technology.) For each item below, circle the number that represents the level of
relative preference with respect to the criteria. Note: For each pair of strategies, only one scale value

should be circled.

 

Strategy 1

 

 
   
 

Strategy 2

Strong
Very Strong

Very Strong
Equal

' Extreme
- Moderate
Strong

 

vi

a

 

. Maximum Achievable .

Oontml- Technology
(MACT) numerical ‘
emission limit: EPA
determines MACT
emission limit and
leaves thechoice of
control technology to

the m’lltz indu_s§y.
MACT technology
regulation: EPA
determines MACT
emission limit and
promulgates a
technology standard for
the utility industry.

‘ Moderate

 
 
  
  
  
 
 
   
       
       
     
     

 

7.765432123456717
CnteriaComphancefle

  

MACT numerical
emission limit plus
emissions trading: EPA
determines MACT
emission limit and
leaves the strategy for
compliance up to the
utility industry

98765432123456789

Criteria: Compliance flexibility

 

Multi-pollutant
regulation: EPA
establishes and
promulgates emission
standards for multiple
pollutants (e.g. NOx,
C02, 802, and Hg) at
one time.

 

Receptor-based
standard: EPA
establishes and
promulgates emission
standards for single
plants based on specific
pollution contributions.

98765432123456789

Criteria: Compliance flexibility

 

Receptor-based ‘

, standard: EPA

establishes and

standards to:- single

 

79876543212345678
promulgatesemission.

plants based on specific I
pollution contributions, '

 

   

iv Criteria: Compliance flexibility

 

 

 

165

5. Criteria: Planning certainty

For each pair of strategies, using the preference scale provided. please indicate which strategy is preferred
with respect to the criteria planning certainty (level of certainty regarding future pollutant regulations and
pollution control needs). For each item below. circle the number that represents the level of relative
preference with respect to the criteria. Note: For each pair of strategies. only one scale value should be
circled.

 

Strategy 1

MACT technology MACT numerical
regulation: EPA emission limit plus
deterrninesMAC'I‘ 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 emissionstrading:EPA
emission limit and determines MACT
promulgates a Criteria: Planning certainty emission limit and
technology standard for leaves the strategy for
the utility industry. compliance up to the
utility industry
includin tradin

W3“: .

Multi-pollutant

regulation: EPA

establishesand 98765432123456789

promulgates emission promulgates emission

standards for multiple Criteria: Planning certainty standards for single

pollutants (e.g. NOx, plants based on specific
pollution contributions.

 

166

6. Criteria: Political feasibility

For each pair of strategies, using the preference scale provided, please indicate which strategy is preferred
with respect to the criteria Political feasibility (level of political constraints). For each item below, circle
the number that represents the level of relative preference with respect to the criteria. Note: For each pair of
strategies, only one scale value should be circled.

 

Strategy 1 Strategy 2

 

 

 

 

 

MACT numical
emission limit plus
98765432123456789 emissionstradingzfl’A
determines MACT
Criteria: Political feasibility emission limit and
leaves the strategy for
complianceuptothe
utility industry
includin : ‘

‘6
Multi-pollutant
98765432123456789
promulgates emission
Criteria: Political feasibility standards for single
plants based on specific
pollution contributions.

promulgates emission

standards for multiple

pollutants (e.g. NOx,

C02, 802, and Hg) at
e.

one I]

 

167

7. Criteria: Scientific defensibility

For each pair of strategies. using the preference scale provided, please indicate which strategy is preferred
with respect to the criteria scientific defensibility (associated level of scientific certainty). For each item
below. circle the number that represents the level of relative preference with respect to the criteria. Note:
For each pair of strategies, only one scale value should be circled.

 

Strategy 1

Strong
Moderate

MACT technology MACT numerical
regulation: EPA emission limit plus
determinesMACT 98765432123456789 emissionstradingzfl’A
emission limit and determines MACT

promulgates a Criteria: Scientific defensibility emission limit and
technology standard for leaves the strategy for
the utility industry. compliance up to the
utility indusz
inc u ' - '

Receptor-based
standard: EPA
98765432123456 establishesand

promulgates emission promulgates emission
standards for multiple Criteria: Scientific defensibility standards for single
pollutants (e.g. N0x, plants based on specific
C02, 802, and Hg) at pollution contributions.
one time.

 

168

8. Criteria: Legal feasibility

For each pair of strategies, using the preference scale provided. please indicate which strategy is preferred
with respect to the criteria legal feasibility (need for new or modified laws). For each item below, circle the
number that represents the level of relative preference with respect to the criteria. Note: For each pair of
strategies, only one scale value should be circled.

 

StrategyI Strategy2

Extreme

MACT numerical
emission limit plus
98765432123456789 emissionstrading:EPA
emission limit and determines MACT
promulgates a Criteria: Legal feasibility emission limit and
technology standard for leaves the strategy for
the utility industry. compliance up to the
utility industry
includin tradin

e ...:
Multi pollutant
regulation: EPA .
establishesand 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 establishesand
promulgates emission promulgates emission
standards for multiple Criteria: Legal feasibility standards for single
pollutants (e.g. N0x, plants based on specific
C02. 502, and Hg) at pollution contributions.

 

169

9. Criteria: Cost-benefit

For each pair of strategies, using the preference scale provided, please indicate which strategy is preferred
with respect to the criteria cost-benefit (degree of benefit compared to cost). For each item below, circle
the number that represents the level of relative preference with respect to the criteria. Note: For each pair of
strategies, only one scale value should be circled.

 

Strategy 1

Very Strong
Very Strong

; : t “"‘-a.' ‘9‘“- ‘
MACTtec nology MACT numerical
regulation: EPA emission limit plus
detemiines MACT 9 8 7 6 5 4 3 2 1 2 3 4 5 6 7 8 9 emissions trading: EPA
emission limit and determines MACT
promulgates a Criteria: Cost-benefit emission limit and
technology standard for leaves the strategy for
the utility industry. compliance up to the

utility industry
includin_ tradi -

Receptor-based
standard: EPA
98765432123456789 establishesand
promulgates emission
Criteria: Cost-benefit standards for single
plants based on specific
. llution contributions.
3541'

Multi—pollutant
regulation: EPA
establishes and
promulgates emission
standards for multiple
pollutants at one time.

 

170

Thank you for your participation in this study.

If you would like to make any additional comments, please use the space below:

171

 

APPENDIX V

REMINDER POSTCARD

 

Just a reminder...
'9

You were recently mailed a questionnaire to identify your
preferred strategy for controlling mercury emissions from
coal-fired power plants. If you have already completed and
returned the questionnaire, I would like to take this
opportunity to thank you for your participation.

  

For those that have not yet returned the survey. please remember that the
response deadline is June 1, 2001. Because you have been identified as an
expert in this research area, I'm sure you understand the importance of the topic
and how critical your participation is in helping me approach this issue in a
comprehensive and informed manner.

Thank you in advance for your help with and support of my research endeavor.
Julie Metty, MS Candidate

Michigan State University
51 7/371 -7443

 

172

 

REFERENCES

Agency for Toxic Substances and Disease Registry. 1999. Toxicological profile for
mercury (Update). Research Triangle Park: Research Triangle Institute.

Akagi, H., P. Grandjean, Y. Takizawa, and P. Weihe. 1998. Methylmercury dose
estimation from umbilical cord concentrations in patients with Minamata disease.
Environ. Res. 77(2):98-103.

American Council for and Energy-Efficient Economy. 2000. State Scorecard on Utility
Energy Efficiency Programs. Washington, DC.

American Sportsfishing Association. 1998. “The Economic Importance of Sport
Fishing.” Alexandria.

Arrow, Kenneth J. 1986. Social Choice and Multi—criterion Decsision-making.
Cambridge: MIT Press.

Axtel], C.D., GJ. Myers, P.W. Davidson, A.L. Choi, E. Cemichiari, J. Sloane-Reeves, C.
Cox, C. Shamlaye, and T.W. Clarkson. 1998. Semiparametric modeling of age at
achieving developmental milestones after prenatal exposure to methylmercury in the

Seychelles child development study. Environmental Health Perspectives.
106(9):559-564.

Barbosa, A.C., S.R.L. Silva, and J .G. Dorea. 1998. Concentration of mercury in hair of
indigenous mothers and infants from the Amazon basin. Archives of Environmental
Contamination and Toxicology 34: 100-105.

Bazerman, Max H., David M. Messick, Ann E. Tenbrunsel, and Kimberly A. Wade-
Benzony. 1997. Environment, Ethics, and Behavior. San Francisco.

Beinat, Euro and Peter Nijkamp. 1998. Multicriteria Analysis for Land-Use
Management. The Netherlands.

Berry, Rita. 1999. Collecting data by in-depth interviewing. Paper presented at the
British Educational Research Association Annual Conference, September 2-5, at
University of Sussex, Brighton.

Carlsson, Christopher, and Pirkko Walden. 1995. AHP in Political Group Decisions: A
Study in the Art of Possibilities. Interfaces 25(4): 14-29.

Carpi, A. 1997. Mercury and Combustion Sources: A Review of chemical species and
their transport in the atmosphere. Water, Air, and Soil Pollution 98:241—254.

173

Center for Clean Air Policy (CCAP). 1998. Mercury Emissions from Coal-Fired Power
Plants: Science, Technology, and Policy Options. Washington, DC.

Clarkson, T.W. 1992. Major issues in environmental health. Environmental Health
Perspectives 100:31-38.

Cordier, S. and M. Care]. 1999. Neurotoxic Risks in Children Related to Exposure to
Methylmercury in French Guiana. IN SERM U170 and U149 - Study financed by the
Health Monitoring Institute (RNSP). National Institute of Health and Medical
Research. April.

Counter, S.A., L.H. Buchanan, G. Laurel], and F. Ortega. 1998. Blood mercury and
auditory neuro-sensory responses in children and adults in the Nambija gold mining
area of Ecuador. Neurotoxicology l9(2):l85-196.

Crump KS, et al. 2000. Benchmark concentrations for methylmercury obtained from the
Seychelles Child Development Study. Environ Health Perspect 108(3):257-63.

Davidson, P. W., G]. Myers, C. Cox, C. Axtell, C. Shamlaye, J. Sloan-Reeves, E.
Cemichiaru, L. Needham, A.Choi, Y. Wang, M. Berlin, and T.W. Clarkson. 1998.
Effects of prenatal and postnatal methylmercury exposure from fish consumption on
neurodevelopment. Journal of the American Medical Association. 280(8):701-707.

Davidson, P. W., 6.]. Myers, C. Cox, C.F. Shamlaye, D.O. Marsh, M.A. Tanner, M.
Berlin, J. Sloan-Reeves, E. Cemichiaru, O. Choisy, A.Choi, and T.W. Clarkson.
1995. Longitudinal neurodevelopmental study of Seychellois children following in
utero exposure to methylmercury from maternal fish ingestion: outcomes at 19 and
29 months. Neurotoxicology. l6(4):677-688.

Enstrom, DR. and EB. Swain. 1997. Recent declines in atmospheric mercury deposition
in the upper Midwest. Environmental Science and Technology 31:960-967.

Evers, D.C., J.D. Kaplan, M.W. Meyer, P.S. Reams, W.E. Braselton, A. Major, N.
Burgess, and A.M. Schuehammer. 1998. Geographic trend in mercury measured in
common loon feathers and blood. Environmental Toxicology and Chemistry

17(2): 173-183.

Fisher, R.; Ury, W.; and B. Patton. 1991. Getting to Yes: Negotiating Agreement Without
Giving In. 2“d Edition. New York: Penguin Books.

Fitzgerald, W.F., D.R. Engstrom, R.P. Mason, and EA. Nater. 1997. The case for
atmospheric mercury contamination in remote areas. Environmental Science and
Technology 32( l ): 1-7.

Grandjean, Pl, P. Weihe, R.F. White, F. Debes, S. Araki, K. Yokoyama, K. Murata, N.
Sorensen, R. Dahl, and R]. Jorgensen. 1997. Cognitive Deficit in 7-Year—Old

174

Children with Prenatal Exposure to Methylmercury. Neurotoxicology and
Teratology 19(6):4l7—428.

Grandjean, Pl, P. Weihe, R.F. White. 1995. Milestone development in infants exposed to
methylmercury from human milk. Neurotoxicology 13(1):27-34.

Great Lakes Commission (GLC). 1999. Great Lakes Regional Air Toxic Emissions
Inventory: Initial Inventory Using 1993 Data. Ann Arbor.

Hamalainen, Raimo P. 1990. A Decision Aid in the Public Debate on Nuclear Power.
European Journal of Operational Research 48: 66-76.

Harada, M., H. Akagi, T.Tsuda, T. Kizaki, H. Ohno. 1999. Methylmercury level in
umbilical cords from patients with congenital Minamata disease. Sci. Total Environ.
234(1-3):59-62.

Harada, M. 1995. Minamata disease: Methylmercury poisoning in Japan caused by
environmental pollution. Crit. Rev. Toxicol.25:l-24

Health Canada. 1995. Assessment of Mercury Exposure and Risks from Dental
Amalgam, 1995, Final Report. Ottawa.

Hoyer, M., J. Burke, and G Keeler. 1995. Atmospheric sources, transport, and
deposition of mercury in Michigan: Two years of event precipitation. Water, Air,
and Soil Pollution 80: 199-208.

Jackson, T. A. 1997. Long-range atmospheric transport of mercury to ecosystems, and
the importance of anthropogenic emissions- a critical review and evaluation of the
published evidence. Environmental Review 5:99-120.

Kahneman, Daniel, Jack L. Knetsch, and Richard H. Thaler. 1990. Experimental Tests
of the Endowment Effect and the Coase Theorem. The Journal of Political Economy
98(6): 1325-1348).

Kahnemen, Daniel and Amos Tversky. 1979. Prospect Theory: An Analysis of Decision
under Risk. Econometrica 47: (263-291).

Kangas, Jyrki, Ron Store, Pekka Leskinen, and Lauri Mehtatalo. Improving the Quality
of Landscape Ecological Forest Planning by Utilising Advanced Decision Support
Tools. Forest Ecology and Management 132: 157-171.

Kjellstrom, T. P. Kennedy, S Wallis, and C. Mantel]. 1986. Physical and Mental
Development of Children with Prenatal Exposure to Mercury from Fish. Stage 1.:
Preliminary tests at age 4. National Swedish Environmental Protection Board Report
3080. Solna Sweden.

175

Kjellstrom, T. P. Kennedy, S Wallis, A Stewrt, L. Friberg, B. Lind, T. Wutherspoon, and
C. Mantel]. 1989. Physical and Mental Development of Children with Prenatal
Exposure to Mercury from Fish. National Swedish Environmental Protection Board

Report No. 3642.

Knetsch, Jack L. 1997. Reference States, Fairness, and Choice of Measure to Value
Environmental Changes. Environment, Ethics, and Behavior. San Francisco.

Koster, M.D., D.P. Ryckman, D.V.C. Weseloh, and J. Struger. 1996. Mercury levels in
Great Lakes herring gull eggs, 1972-1992. Environmental Pollution 93(3):261-270.

Lebel, J., D. Mergler, M. Lucote, M. Amorim, J. Dolbec, D. Miranda, G. Arantes, I.
Rheault, and P. Pichet. 1996. Evidence of early nervous system dysfunction in
Amazonian populations exposed to low-levels of methylmercury. Neurotoxicology
17(1): 157-167.

Leung, PingSun, Jill Muraoka, Stuart T. Nakamoto, and Sam Pooley. 1998. Evaluating
Fisheries Management Options in Hawaii Using Analytic Hierarchy Process (AHP).
Fisheries Research 36: 171-183.

Marsh, D.O., MD. Turner, J.C. Smith, P. Allen, and N. Richdale. 1995. Fetal
methylmercury study in a Peruvian fish-eating population. Neurotoxicology
16(4):7 17-726.

Mason, RR, and K.A. Sullivan. 1997. Mercury in Lake Michigan. Environmental
Science and Technology 31:942-947.

Mason, R.P., W.F. Fitzgerald. and F. M. More]. 1994. The biogechemical cycling of
elemental mercury: Anthropogenic influences. Geochimica et Cosmochimica Acta
58(15):3191-3198.

McKeown-Eyssen, G.E., J. Ruedy, and A. Neims. 1983. Methyl mercury exposure in
northern Quebec. H. Neurologic findings in children. American Journal of
Epidemiology 1 18(4): 470-479.

Mendoza, Guillermo A., and R. Prabhu. 2000. Multiple Criteria Decision Making
Approaches to Assessing Forest Sustainability Using Criteria and Indicators: A Case
Study. Forest Ecology and Management 131: 107-126.

Meyer, M.W., D.C. Evers, and WE. Braselton. 1995. Common Loons (Gavia immer)
Nesting on Low pH Lakes in Northern Wisconsin Have Elevated Blood Mercury
Content. Water, Air, and Soil Pollution 80: 871-880.

Michigan Department of Community Health (MDCH). 2000. Michigan 2000 Fish
Advisory. Lansing.

176

Michigan Mercury Pollution Prevention Task Force (M2P2). 1996. Mercury Pollution
Prevention in Michigan: Summary of Current Efforts and Recommendations for
Future Activities. Lansing.

Minnesota Pollution Control Agency (MPCA). 2000. Options and Strategies for
Reducing Mercury Releases. St. Paul.

Morrison, Gwendolyn C. 1997. Willingness to pay and willingness to accept: some
evidence of an endowment effect. Applied Economics 29: (411-417).

Murata, K., P. Weihe, A. Renzoni, F. Debes, R. Vasconcelos, F. Zino, S. Araki, P.J.
Jorgensen, R.f. White, and P. Grandjean. 1999. Delayed evoked potentials in

children exposed to methylmercury forom seafood. Nerotoxcioc. Teratol 21(4):343-
348.

Myers, G.J., P.W. Davidson, C.F. Shamlaye, C.D. Axtell, E. Cemichiari, O. Choisy, A.
Choi, C. Cox, and T.W. Clarkson. 1997. Effects of prenatal methylmercury expousre
from a high fish diet on developmental milestones in the Seychelles Child
Development Study. Neurotoxicology 18(3):819-830.

Myers, G.J., D.O. Marsh, C. Cox, P.W. Davidson, C.F. Shamlaye, M.A. Tanner, A. Choi,
E. Cemichiari, O. Choisy, and T.W. Clarkson. 1995a. A pilot neurodevelopmental
study of Seychellois children following in utero exposure to methylmerucyr from a
maternal fish diet. Neurotoxicology l6(4):629-638.

Myers, G.J., D.O. Marsh, P.W. Davidson, C. Cox, C.F. Shamlaye, M. Tanner, A. Choi, E.
Cemichiari, O. Choisy, and T.W. Clarkson. 1995b. Main neurodevelopmental study
of Seychellois children following in utero exposure to methylmercury from a
maternal fish diet: Outcome at six months. Neurotoxicology l6(4):653-664.

National Center for Environmental Decision-Making Research (NCEDR). 1996. The
Nature and Challenges of Enviommental Decision Making: Case Studies for Policy
Improvement. Knoxville.

National Research Council (NRC). 2000. Toxicological Efi'ects of Methylmercury.
Washington, DC: National Academy Press.

National Wildlife Federation (NWF). 1997. Ohio ’s Mercury Menace. Ann Arbor.

 

2000. Mercury-Free Medicine Campaign's Pledged Hospitals & Clinics.
http://www.noharm.org/.

Nierenberg, D.W., R.E. Nordgren, M.B. Chang, R.W. Siegler, M.B. Blayney, F.
Hochberg, T.Y. Toribara, and E. Cemichiari. 1998. Delayed cerebellar disease and

death after accidental exposure to dimethylmercury. New England Journal of
Medicine 338 (23): 1672.

177

Nriagu, J .0., ed. 1979. The Biogeochemistry of Mercury in the Environment.
Amsterdam; New York: Elsevier/North-Holland Biomedical Press; New York: sole
distributors for the US. and Canada, Elsevier/North-Holland.

Parakan, Celik, and Ming-Lu Wu. 2000. “Comparison of Three Modern Multicriteria
Decision-Making Tools.” International Journal of Systems Science 31(4): 497—517.

Physicians for Social Responsibility, 1998. Fact Sheet: Environmental Mercury Exposure
and Human Health. Washington DC.

Perman, Roger, Yue Ma, and James McGilvray. 1996. Natural Resource &
Environmental Economics. London and New York.

Ra, Jang W. 1999. “Chainwise Paired Comparisons.” Decision Science 30(2): 581-599.
Raloff, J. 1991. Mercurial Risks from Acid’s Reign. Science News 139:152-166.

Rice, Deborah. 1995. Neurotoxicity of Lead, Methylmercury, and PCBs in Relation to
the Great Lakes, Environmental Health Perspectives 103(Suppl. 9):71-87.

Saaty, Thomas L. 1994. "How to Make a Decision: The Analytic Hierarchy Process."
Interfaces 24(6): 19-43

Saaty, Thomas L. 1990. “How to Make a Decision: The Analytic Hierarchy Process."
European Journal of Operational Research 48: 2-8.

Saaty, Thomas L. 1980. The Analytic Hierarchy Process. McGraw-Hil] International,
New York, NY, USA.

Shannon, JD. and EC. Voldner. 1995. Modeling atmospheric concentrations of
mercury and deposition to the Great Lakes. Atmospheric Environment 29:1649-
1661.

Stein, E. D., Y. Cohen, A.M. Winer. 1996. Environmental distribution and
transformation of mercury compounds. Critical Reviews in Science and Technology
26(1)l-43.

Steuerwald, U., P. Weihe, P. Jorgensen, K. Bjerve, J. Brock, B. Heinzow, E. Budtz-
Jorgensen, and P. Grandjean. 2000. Maternal seafood diet, methylmercury exposure,
and neonatal neurological function. J. Pediatr. 136(5):599-605.

Susskind, L.; Levy, PL; and J. Thomas-Larrner. 2000. Negotiating Environmental
Agreements. Washington, DC: Island Press.

178

 

 

 

 

Thompson, Leigh L. and Richard Gonzalez. 1997. Environmental Disputes:
Competition for Scarce Resources and Clashing of Values. Environment, Ethics, and
Behavior. San Francisco.

United States Department of Energy (DOE). 2000. News Release: New Projects
Positioning Coal-Fired Utilities to Meet Possible Mercury Control Standards with
New, Lower Cost Technologies. Washington, DC.

 

1997. US. Electric Utility Demand Side Management 1996. DOE/BIA-
0589(96). Washington, DC.

United States Environmental Protection Agency (EPA). 1997a. Mercury Study Report to
Congress, Volume II: An Inventory of Anthropogenic Mercury Emissions in the
United States. EPA—452/R-97-004. Washington DC. Available:
http://www.epa.gov/oar.mercury.html.

 

. 1997b. Mercury Study Report to Congress, Volume III: Fate and Transport of
Mercury in the Environment. EPA-452/R-97-005. Washington DC. Available:
http://www.epa.gov/oar.mercury.html.

 

1997c. Mercury Study Report to Congress, Volume VII: Characterization of
Human Health and Wildlife Risks from Mercury Exposure in the United States.
EPA-452/R-97-009. Washington DC. Available:
http://www.epa.gov/oar.mercury.html.

l997d. Mercury Study Report to Congress, Volume VIII: An Evaluation of
Mercury Control Technologies and Costs. EPA-452/R-97-0010. Washington DC.
Available: http://www.epa.gov/oar.mercury.html.

. 1998. Study of Hazardous Air Pollutant Emissions from Electric Utility Steam
Generating Units — Final Report to Congress. EPA-453/R-98-004 a and b.

. 1999a. Fact Sheet - Update: National Listing of Fish and Wildlife Advisories.
Office of Water. EPA 823-F-99-005. Washington, DC. Available: http://fish.rti.org

. 1999b. Information Collection Request

. 19990. The National Survey of Mercury Concentrations in Fish. EPA-823-R-
99-014. Washington DC. Available: http://www.epa.gov/ost/fish/ mercurydatapdf

. l999d. Fact Sheet: Air Pollution and Water Quality: Atmospheric Deposition
Initiative: Where is the Air Pollution Coming From? Washington DC.

2000a. Great Lakes Binational Toxics Strategy Draft Report for Mercury

Reduction Options, [Online]. Chicago, IL. Available:
http://www.epa.gov/RegionS/air/mercury/ mercury.html

179

 

 

. 2000b. Mercury Reduction Activities Reported from Around the Great Lakes,
[Online]. Washington DC. Available:
http://www.epa.gov/glnpo/bnsdocs/stakeholders1198/ mercsuccesshtml.

United States Food and Drug Administration (FDA). 1994 (revised 1995). “Mercury In
Fish: Cause For Concern?” FDA Consumer. September

Vargas, Luis G. 1990. “An Overview of the Analytic Hierarchy Process and its
Applications.” European Journal of Operational Research 48: 2-8.

Watanabe, C. and H. Satoh. 1996. Evolution of our understanding of methylmercury as
a health threat, Environmental Health Perspectives 104(Supp]. 2):367-379.

Zeleny, Milan. 1982. Multiple Criteria Decision Making. New York: McGraw-Hill
Book Co.

180